MATH 0011. Data Science for All

Units: 4
Prerequisite: Completion of Intermediate Algebra or equivalent with grade of "C" or better, or appropriate placement
Hours: 108 (54 lecture, 54 laboratory)
Designed for students from any major, provides high-level understanding of how data, statistics, and inference are inter-related. Introduces the core concepts of data science, including statistical inference and computational thinking. Teaches critical concepts and skills in computer programming and statistical inference while working with real data, such as economic data, geographic data, and social networks. Prepares students to make more data-driven decisions, gaining experience with machine learning and with the practical application of statistical concepts like hypothesis testing, confidence intervals via bootstrapping, regression, inference for regression, and predictive modeling while considering the social issues surrounding data privacy and data ownership. (C-ID MATH 110) (CSU, UC)

MATH 0011 - Data Science for All

https://catalog.sierracollege.edu/course-outlines/math-0011/

Catalog Description Prerequisite: Completion of Intermediate Algebra or equivalent with grade of "C" or better, or appropriate placement Hours: 108 (54 lecture, 54 laboratory) Description: Designed for students from any major, provides high-level understanding of how data, statistics, and inference are inter-related. Introduces the core concepts of data science, including statistical inference and computational thinking. Teaches critical concepts and skills in computer programming and statistical inference while working with real data, such as economic data, geographic data, and social networks. Prepares students to make more data-driven decisions, gaining experience with machine learning and with the practical application of statistical concepts like hypothesis testing, confidence intervals via bootstrapping, regression, inference for regression, and predictive modeling while considering the social issues surrounding data privacy and data ownership. (C-ID MATH 110) (CSU, UC) Course Student Learning Outcomes CSLO #1: Apply numerical methods of descriptive statistics and probabilistic concepts using sampling method to extract relevant information. CSLO #2: Interpret data by analysis, draw meaningful conclusions while considering ethics and privacy, and present their findings effectively using various types of graphs. CSLO #3: Create computer scripts for data manipulation, visualization, classification and numerical representation. CSLO #4: Conduct various statistical techniques, such as hypothesis testing, estimating a parameter using confidence intervals, linear regression and correlation, chi-squared tests, and one-way analysis of variance (ANOVA). Effective Term Fall 2025 Course Type Credit - Degree-applicable Contact Hours 108 Outside of Class Hours 108 Total Student Learning Hours 216 Course Objectives Upon Successful completion of the course, students will be able to: Explore various methods for data acquisition and assess their respective strengths and weaknesses; Interpret and describe data displayed in tables; Analyze and interpret data trends, both visually through graphs and numerically; Address potential biases and unintended outcomes inherent in machine learning processes when working with datasets; Compute and interpret key statistical measures such as central tendency and dispersion for given datasets; Explain the central role of variability in statistical analysis and its implications; Apply fundamental probability principles, including sample space concepts and probability rules; Compute the mean and variance for discrete distributions to understand their distributional characteristics; Calculate and interpret probabilities using binomial, normal, and t-distributions in various contexts; Differentiate between sample and population distributions and analyze the significance of the Central Limit Theorem in statistical inference; Choose the most suitable inferential statistics method for resolving a given statistical problem and guiding decision-making; Develop and explain confidence intervals for estimating means and proportions in one or two populations; Execute hypothesis testing procedures for means and proportions in one or two populations and interpret the outcomes; Determine and interpret the significance levels, including interpreting p-values; Identify and describe Type I and II errors in statistical inference processes; Conduct an analysis of variance (ANOVA) and interpret results; Perform and interpret the result of the chi-squared goodness-of-fit test; Conduct a linear regression analysis and apply the findings to make accurate predictions; Compose code to perform various statistical analysis numerically and visually; and Apply appropriate statistical methods to analyze, ethically interpret, and communicate findings based on real-world data from diverse disciplines, such as business, economics, education, psychology, and the social and life sciences. General Education Information Approved College Associate Degree GE Applicability AA/AS - Mathematical Concepts and Quantitative Reasoning CSU GE Applicability (Recommended-requires CSU approval) Cal-GETC Applicability (Recommended - Requires External Approval) Cal-GETC 2 - Mathematical Concepts IGETC Applicability (Recommended-requires CSU/UC approval) Articulation Information CSU Transferable UC Transferable Methods of Evaluation Objective Examinations Example: Economic study: Minimum Wage and Unemployment Rates 1. In an economic study investigating the impact of minimum wage increases on unemployment rates, researchers collect data from different regions over several years. They aim to determine if there is a significant relationship between minimum wage hikes and changes in unemployment levels. After conducting hypothesis testing, the researchers find a p-value of 0.03, which is below the significance level of 0.05. What can be concluded from this result regarding the significance level and interpretation of the p-value in the context of the study? A) The significance level represents the probability of making a Type I error, while the p-value indicates the probability of making a Type II error. B) The significance level is the threshold for rejecting the null hypothesis, typically set at 0.05 or 0.01, while the p-value measures the strength of evidence against the null hypothesis. C) The significance level is calculated as 1 minus the p-value, representing the confidence level of the hypothesis test. D) The significance level is determined by the sample size, while the p-value is determined by the test statistic. Problem Solving Examinations Example: Comparing Chances: Online Grocery Shopping In the United States, 28% of adults use Instacart for online grocery shopping. Suppose you sample US adults randomly so that each sampled adult has a chance 0.28 of being a Instacart user independently of all the others. (a) For which sample size below is there a higher chance that the percent of Instacart users in the sample will be at least 25%? # 200, 400 (b) For which sample size below is there a higher chance that the percentage of Instacart users in the sample will be at least 50%? # 200, 400 (c) For which sample size below is there a higher chance that the percentage of Instacart users in the sample will be at least 25% but less than 50%? # 200, 400 (d) (Briefly explain your choices in Parts (a)-(c). Grading: This problem is graded for correctness and meaningful justification for their choices. Projects Example: Project Title: Analysis of Housing Prices in a Metropolitan Area Problem Statement: The housing market in a metropolitan area has experienced fluctuations in prices over the past few years. Homebuyers, sellers, and real estate investors are keen to understand the factors influencing these price fluctuations and predict future trends. The objective of this project is to analyze historical housing data, identify key factors affecting housing prices, and develop a predictive model to forecast future prices. Project Objectives: • Explore and clean the housing dataset to ensure data quality and integrity. • Conduct exploratory data analysis to uncover patterns, trends, and relationships among housing variables. • Identify relevant features such as location, property type, size, amenities, and economic indicators that impact housing prices. • Build regression models to predict housing prices based on selected features. • Evaluate model performance using appropriate metrics and techniques. • Interpret model results and identify significant predictors of housing prices. • Develop actionable insights and recommendations for homebuyers, sellers, and real estate professionals based on the analysis. Project Tasks: • Data Collection: Gather historical housing data from reliable sources such as real estate databases or government agencies. • Data Preprocessing: Clean and preprocess the dataset, handle missing values, and encode categorical variables. • Exploratory Data Analysis: Explore the dataset using descriptive statistics, visualizations, and correlation analysis to understand the relationships between variables. • Select Features: Select relevant features that are likely to influence housing prices. • Model Development: Build linear regression model to predict housing prices. • Model Evaluation: Assess model performance using metrics such as correlation coefficient and mean squared error. • Interpretation and Visualization: Interpret model coefficients, feature importance, and visualize key findings using graphs and charts. • Recommendations: Provide actionable insights and recommendations for homebuyers, sellers, and real estate professionals based on the analysis. This project will provide students with hands-on experience in data preprocessing, exploratory data analysis, regression modeling, and interpretation of results in the context of real estate market analysis. Students have the option to collaborate with a partner on this project. They can discuss the project with classmates or seek guidance during office hours from the instructor. However, sharing the code with anyone other than their partner is prohibited. Repeatable No Methods of Instruction Laboratory Lecture/Discussion Distance Learning Lab: Data science entails analyzing real-world datasets, necessitating a series of labs and projects utilizing authentic data as integral components of the course. For each lab or project, students have the option to collaborate with one partner. The instructor will be accessible virtually during designated student hours to address queries and provide assistance. Students will have the opportunity to message the instructor for guidance if they are unable to attend the designated student hour. Projects are submitted online, and feedback will be provided by the instructor using a rubric. Healthy Living: We will investigate one of the major causes of death in the world: cardiovascular disease. It has two parts. • In Part 1, we'll investigate the major causes of death in the world during the past century (from 1900 to 2015). In order to get a better idea of how we can most effectively prevent deaths, we need to first figure out what the major causes of death are. Run the following cell to read in and view the causes_of_death table, which documents the death rate for major causes of deaths over the last century (1900 until 2015). • In Part 2, we'll look at data from the Framingham Heart Study, an observational study into cardiovascular health. Students will examine one of the main findings of the Framingham study: an association between serum cholesterol (i.e., how much cholesterol is in someone's blood) and whether or not that person develops heart disease using the hypothesis test. We will use the following null and alternative hypotheses: • Null Hypothesis: In the population, the distribution of cholesterol levels among those who develop heart disease is the same as the distribution of cholesterol levels among those who do not. • Alternative Hypothesis: The cholesterol levels of people in the population who develop heart disease are higher, on average, than the cholesterol level of people who do not. Lecture: Lesson plan: Example-1: Instructor will design a lesson plan that enables students to successfully complete complex lab assignments centered around real-world application problems. Begin with straightforward examples to stimulate discussion and foster critical thinking, thereby preparing students to tackle more advanced problems. This assignment will be delivered through interactive computing environment. Let's start with a simple example to help you to complete more complex examples about disease in your next lab. Imagine you are a marble. You don't know what you look like (since you obviously have no eyes), but you know that Samy drew you uniformly at random from a bag that contained the following marbles: 4 large shiny marbles, 1 large dull marble, 6 small shiny marbles, and 2 small dull marbles. Question- Knowing only what we've told you so far, what's the probability that you are a large shiny marble? (click on each cell below to see the table, value or graph) probability_large_shiny = ... Here's a table with those marbles: marbles = Table.read_table("marbles.csv") marbles.show() Here are the counts of each type of marble in a pivot table. marbles.pivot('surface', 'size') Here are all the different combinations of surface and size, with the count for each surface-size combination. Each type of marble appears in its own row. marbles.group(['surface', 'size']) Question- What's the probability that you're a shiny marble? Calculate this by hand (using programming tool for arithmetic) by looking at your icon array. Conditional probability: Suppose you overhear Samy say that you are a large marble. Does this somehow change the chance that you are shiny? Let's find out. Question- What's the probability you are a shiny marble, knowing that you are a large marble? Question- Suppose instead Samy had said you are a shiny marble (hooray!). What's the probability that you're large? Run the code cell below to display the icon array, then assign probability_large_given_shiny to the appropriate value. Question- Can you answer the previous two questions just by looking at the full icon array? Hopefully the icon arrays from the above example helped you build intuition for why conditional probabilities can be helpful. Now, let’s look at a real-life application. Example-2: The instructor will develop a lesson plan centered around textbook readings to encourage self-directed learning through discussion. Discussion will be conducted through LMS while completing the problem through interactive computing environment. Instructor will provide guidance whenever needed. This discussion is based on textbook reading and an interesting example inspired by a mathematical theorem called "Infinite monkey theorem" (https://en.wikipedia.org/wiki/Infinite_monkey_theorem), which postulates that if you put a monkey in the situation described above for an infinite time, they will eventually type out all of Shakespeare’s works. Read the three topics from chapter "Probability, Simulation, Estimation, and Assessing Models". Randomness Sampling and Empirical Distributions Testing Hypotheses Monkeys Typing Shakespeare: A monkey is banging repeatedly on the keys of a keyboard. Each time, the monkey is equally likely to hit any of the 26 lowercase letters of the English alphabet, 26 uppercase letters of the English alphabet, and any number between 0-9 (inclusive), regardless of what it has hit before. There are no other keys on the keyboard. Question Suppose the monkey hits the keyboard 5 times. Compute the chance that the monkey types the sequence Math1 (Call this data_chance.) Use algebra and type in an arithmetic equation that your program can evaluate. Question Write a function called simulate_key_strike. It should take no arguments, and it should return a random one-character string that is equally likely to be any of the 26 lower-case English letters, 26 upper-case English letters, or any number between 0-9 (inclusive). Question Write a function called simulate_several_key_strikes. It should take one argument: an integer specifying the number of key strikes to simulate. It should return a string containing that many characters, each one obtained from simulating a key strike by the monkey. Hint: If you make a list or array of the simulated key strikes called key_strikes_array, you can convert that to a string by calling "".join(key_strikes_array) Question Call simulate_several_key_strikes 5000 times, each time simulating the monkey striking 5 keys. Compute the proportion of times the monkey types "Math11", calling that proportion data_proportion. Question Check the value your simulation computed for data_proportion. Is your simulation a good way to estimate the chance that the monkey types "Math11" in 5 strikes (the answer to question 1)? Why or why not? Question Compute the chance that the monkey types the letter "t" at least once in the 5 strikes. Call it t_chance. Use algebra and type in an arithmetic equation that program can evaluate. Question Do you think that a computer simulation is more or less effective to estimate t_chance compared to when we tried to estimate data_chance this way? Why or why not? Distance Learning Discussion Forums: Students are encouraged to engage in discussions with their peers on each question, refraining from sharing their code. They can discuss mathematical concepts like "absolute value" and "proportion" to bridge gaps in their understanding. Discussions may be anonymized to facilitate open questioning without apprehension. Instructors will introduce specific topics to promote active learning. Instructor will initiate certain topics to enhance the active learning. Example: Discussion based on a virtual homework problem. Birth rate and death rate: The following table gives census-based population estimates for each state on both July 1, 2015 and July 1, 201 The last four columns describe the components of the estimated change in population during this time interval. For all questions below, assume that the word "states" refers to all 52 rows including Puerto Rico & the District of Columbia. The data was taken from censos.gov Run the cell below to clean the table and make it easier to work with. (A set of code will be provided to the students to generate the data.) Question Assign us_birth_rate to the total US annual birth rate during this time interval. The annual birth rate for a year-long period is the total number of births in that period as a proportion of the population size at the start of the time period. Hint: Which year corresponds to the start of the time period? us_birth_rate = … us_birth_rate Question Assign movers to the number of states for which the absolute value of the annual rate of migration was higher than 1%. The annual rate of migration for a year-long period is the net number of migrations (in and out) as a proportion of the population size at the start of the period. The MIGRATION column contains estimated annual net migration counts by state. Question Assign west_births to the total number of births that occurred in region 4 (the Western US). Hint: Make sure you double check the type of the values in the region column, and appropriately filter (i.e. the types must match!). Question Assign less_than_west_births to the number of states that had a total population in 2016 that was smaller than the total number of births in region 4 (the Western US) during this time interval. Question 5 : Create a visualization to understand the relationship between birth and death rates. The annual death rate for a year-long period is the total number of deaths in that period as a proportion of the population size at the start of the time period. What visualization is most appropriate to see if there is an association between birth and death rates during a given time interval? Scatter Plot Line Graph Bar Chart Assign visualization below to the number corresponding to the correct visualization. Question In the code cell below, create a visualization that will help us determine if there is an association between birth rate and death rate during this time interval. It may be helpful to create an intermediate table here. Question True or False: There is an association between birth rate and death rate during this time interval. Assign assoc to True or False in the cell below. Instructor will provide the submission instructions. Typical Out of Class Assignments Reading Assignments Weekly reading will be assigned based on the topics covered each week. The Textbook readings will include topics like various types of experimental study, four ways of classifying reality and the result of the test, how to construct confidence interval, and testing hypothesis, analyzing graphical and numerical data summaries, and identifying data characteristics appropriate for machine leaning techniques such as classification. Also, the textbook guide students through the sample programming exercises. Example 1. Read section "Why mean matters?" from the textbook and be prepare to discuss about the following questions. What exactly does the mean measure? How close is the mean to the most of the data? How does the sample size affect the variability of the sample mean? Why does empirical distributions of random sample means exhibit a bell-shaped curve? Writing, Problem Solving or Performance Writing assignments will be part of homework, lab and project which include summarizing and analyzing real-world data. Example: 1. Homework: Scary Arithmetic An ad for ADT Security Systems says, "When you go on vacation, burglars go to work [...] According to FBI statistics, over 25% of home burglaries occur between Memorial Day and Labor Day." Does the data in the ad support the claim that burglars are more likely to go to work during the time between Memorial Day and Labor Day? Please explain your answer. Note: You can assume that "over 25%" means only slightly over. Had it been much over, say closer to 30%, then the marketers would have said so. Write your answer here, replacing this text. 2. Programming: The cell below loads an array called president_birth_years. Calling .column(...) on a table returns an array of the column specified, in this case the Birth Year column of the president_births table. The last element in that array is the most recent birth year of any deceased president. Assign that year to most_recent_birth_year. Complete the code given below: president_birth_years = Table.read_table("president_births.csv").column('Birth Year') most_recent_birth_year = ... most_recent_birth_year Finally, assign sum_of_birth_years to the sum of the first, tenth, and last birth year in president_birth_years. sum_of_birth_years = ... Other (Term projects, research papers, portfolios, etc.) Students’ complete projects using suitable tools to analyze real datasets and present their findings. Each project includes a given data set and a project notebook with questions that align with both in-class and out-of-class tasks. Required Materials Computational and Inferential Thinking: The Foundations of Data Science Author: Ani Adhikari, John DeNero, David Wagner Publisher: UC Berkeley Publication Date: 2022 Text Edition: 2 Classic Textbook?: No OER Link: OER: https://inferentialthinking.com/chapters/intro.html Other materials and-or supplies required of students that contribute to the cost of the course.

BIOL 0011 - Concepts of Biology

https://catalog.sierracollege.edu/course-outlines/biol-0011/

Catalog Description Advisory: Eligibility for ENGL C1000 and MATH 12 Hours: 108 (54 lecture, 54 laboratory) Description: Designed for non-life science majors desiring an introductory biology course with a lab. Introduces the main concepts of biology, covering molecular and cell biology, heredity and nature of genes, biotechnology, evolution, diversity of life, and principles of ecology. Students enrolling in BIOL 11 after having taken BIOL 10 will lose credit for BIOL 10. Not recommended for students who have completed BIOL 56 and 56L. (CSU, UC-with unit limitation) Course Student Learning Outcomes CSLO #1: Develop, utilize and evaluate scientific hypotheses through experimentation. CSLO #2: Appraise the relationship between cellular respiration and photosynthesis. CSLO #3: Formulate the correct structure of the main types of cells and diagnose the hypotheses regarding the evolutionary development of those cells. CSLO #4: Assess the role of DNA in living things, construct methods to analyze the patterns of inheritance, and judge the impact of genetic engineering on living things. CSLO #5: Justify the role of evolution in the development of living things, the diversity of living things and judge the effects of humans on living things on earth. Effective Term Fall 2025 Course Type Credit - Degree-applicable Contact Hours 108 Outside of Class Hours 108 Total Student Learning Hours 216 Course Objectives Via written examinations, quizzes, independent projects, and laboratory exercises, the students will Lecture Objectives: 1. Apply the main steps of the scientific method to develop a scientific hypothesis. (Lecture Ia) 2. Identify the variables found in scientific experiments and the roles that they play in testing hypotheses. (Lecture outline Ia) 3. Outline the levels of organization of life from molecular to ecosystem level in a diagram (Lecture outline I). 4. Apply knowledge of the parts of an atom to construct molecules with a lower energy state than the atoms that entered into the bond. (Lecture outline Ib) 5. Describe characteristics of the main organic compounds and consider roles of various organic molecules in living organisms (Lecture outline 1c) 6. Outline the functions of the main components of prokaryotic cells and the components and organelles of eukaryotic cells (Lecture outline Id) 7. Defend why a living cell is the basic unit of life (Lecture outline Id) 8. Describe the behavior of molecules during diffusion both within the solution itself and across a membrane. (Lecture outline Id) 9. Hypothesize how the structure of the cellular membrane enables cells to function. (Lecture outline Id) 10. Differentiate between the first two laws of thermodynamics and apply them to living systems (Lecture outline IIa) 11. Diagram how enzymes work and how they can be shut down. (Lecture outline IIb) 12. Identify the role of enzymes in organisms (Lecture outline IIb) 13. Compare and contrast the processes of photosynthesis and cellular respiration, recognize their role in energy flow in ecosystems. (Lecture outline IIc and IId) 14. Compare and contrast the processes of bacterial fission, mitosis and meiosis, recognize their role in the life cycles of organisms (Lecture outline IIIa) 15. Explain the correlation between errors in the cell cycle and cancer (Lecture outline IIIa). 16. Describe the structure of a DNA molecule and the process by which it replicated. (Lecture outline IIIb) 17. Analyze the main steps of protein synthesis. (Lecture outline IIIb) 18. Critique the role that mutations play in protein synthesis and evolution (Lecture outline IIIb) 19. Identify the main implications of DNA technology in the lives of humans. (Lecture outline IIIb) 20. Judge ethical issues associated with the use of biotechnology. (Lecture outline IIIb) 21. Critique the adaptive significance of sexual reproduction and situations in which asexual reproduction would be preferable. (Lecture outline IIIc) 22. Outline the ways by which meiosis and random fertilization contribute to biological adaptation and diversity.(Lecture outline IIIc) 23. Formulate the main Mendelian rules of inheritance and utilize these rules to solve simple genetic problems (involving monohybrid and dihybrid crosses). (Lecture outline IIIc) 24. Analyze the connection between genetics, heredity, epigenetics and the environment. (Lecture outline IIIc) 25. Evaluate natural selection as the main mechanism of biological evolution. (Lecture outline IVa) 26. Defend the importance of variation, overproduction, and heritability in natural populations. (Lecture outline
IVa) 27. Describe the history of evolutionary thought
(Lecture outline IVa) 28. Compare and contrast microevolution and macroevolution (Lecture outline IVa) 29. Evaluate the Oparin/Miller theory of the origin of life as suggested by geological and biochemical evidence. (Lecture outline IVb) 30. Identify the Domains and Kingdoms recognized by modern taxonomy, list the main characteristics of each domain and kingdom, and give examples of the main representatives of each. (Lecture outline
IV) 31. Evaluate the role that microorganisms, plants, fungi and animals play in ecosystems and in the lives of humans (Lecture outline IV) 32. Investigate the main evolutionary adaptations found in microorganisms, plants, fungi and animals. (Lecture outline IV) 33. Examine the main components of an ecosystem and diagnose the ecological roles that organisms play within them. (Lecture outline IVf) 34. Evaluate the effect of human activities on the diversity of life on and the geological processes of Earth. (Lecture outline
IV) 35. Diagnose the long-term effect of human population growth on the fate of our planet (Lecture outline IV) Laboratory Objectives: 1. Develop, implement and test a scientific hypothesis. (Lab outline I) 2. Construct biological molecules using modeling kits (Lab outline II) 3. Describe characteristics of the main organic compounds and consider roles of various organic molecules in living organisms (Lab outline II) 4. Apply knowledge of the parts of an atom to construct molecules with a lower energy state than the atoms that entered into the bond. (Lab outline II) 5. Outline the functions of the main components (organelles) of a living cell (Lab outline III) 6. Observe the behavior of molecules during diffusion both within the solution itself and across a membrane and determine how factors such as tonicity, molecule size and temperature can play a role in that rate of diffusion. (Lab outline IV) 7. Differentiate between the first two laws of thermodynamics and apply them to living systems (Lab outline IV) 8. Demonstrate via experimentation the role of the molecules involved in the photosynthetic equation. (Lab outline V) 9. Demonstrate via experimentation the role of the molecules involved in the process of both aerobic and anaerobic cellular respiration. (Lab outline VI) 10. Diagram the stages of mitosis outline what occurs during each stage. (Lab outline VII) 11. Describe the structure of a DNA molecule and the process by which it replicated. (Lab outline 12. Analyze the main steps of protein synthesis. (Lab outline VIII) 13. Critique the role that mutations play in protein synthesis and evolution (Lab outline VIII) 14. Isolate DNA from the remains of a living organism. (Lab outline VIII) 15. Formulate the main Mendelian rules of inheritance and utilize these rules to solve simple genetic problems (involving monohybrid and dihybrid crosses). (Lab outline IX) 16. Utilize the rules of natural selection and Mendelian genetics to demonstrate how natural selection affects the gene frequencies of populations. (Lab outline X) 17. Critique the roles that sexual selection, gene flow, genetic drift and mutation play in evolution. (Lab outline X) 18. Investigate the main evolutionary adaptations found in microorganisms, plants, fungi and animals. (Lab outline X, XI, XII, XIII) 19. Apply the metric system when conducting laboratory experiments; correctly and safely use standard tools and equipment (light compound microscope, digital scale, chemical glassware, etc.) in a biology lab. (All labs) 20. Collaborate as a team member during biology lab exercises. (All labs) General Education Information Approved College Associate Degree GE Applicability AA/AS - Life Sciences AS - Life Science Lab CSU GE Applicability (Recommended-requires CSU approval) CSUGE - B2 Life Science CSUGE - B3 Lab Activity Cal-GETC Applicability (Recommended - Requires External Approval) IGETC Applicability (Recommended-requires CSU/UC approval) IGETC - 5B Biological Science IGETC - 5C Laboratory Science Articulation Information CSU Transferable UC Transferable Methods of Evaluation Essay Examinations Example: Answer in a one page, double-spaced essay which will be evaluated based on accuracy and development of response. Rubric grading. 1. Genetically modified organisms are those which have had their genes altered. This is not the same as selective breeding. In selective breeding agriculturalists select the plants or animals that produce the most food and then breed them together to produce offspring that produce a high amount of food. For example, due to selective breeding cows are able to produce more milk per day today than they were in the past. Genetically modified organisms, however are something different. Genetically modified organisms, or GMOs as they are commonly referred to, have genes from other species of organisms inserted into their own genome. For example, Bt corn is a type of corn that has had a gene from a bacterial species called Bacillus thuringiensis inserted into it. This gene makes the corn resistant to a particular corn pest species called the European corn borer. This means that farmers who grow this corn no longer need to spray their corn with pesticides to eliminate this pest. However, there are many who worry about the impact of GMOs on the environment, on humans and on other crop species. What do you think of GMOs? Find some research on-line (from an .org or .edu source) both in support and against the use of these organisms. What do you think of their arguments? Do you agree or disagree? What do you think the global impact of these organisms could be? What percentage of the average American diet is composed of GMOs? Outcomes assessed: 1. Identify the main implications of DNA technology for the medical field and agriculture. (Lecture outline IIIb) 2. Judge ethical issues associated with the use of biotechnology. (Lecture outline IIIb) 2. Answer in a one page, double-spaced essay which will be evaluated based on accuracy and development of response. Rubric grading. In cattle, hornless condition is dominant to horned. If both parents are heterozygous for this condition: a. What is the probability that a calf born to these parents will be horned? b. What is the probability that the calf will be hornless? Outcome Assessed: 1. Formulate the main Mendelian rules of inheritance and utilize these rules to solve simple genetic problems (involving monohybrid and dihybrid crosses). (Lecture outline IIIc) Objective Examinations Example: 1. Hypertrichosis, hairiness of the outer ear, is inherited as a Y-linked recessive in humans, If a man with hypertrichosis marries a woman without the trait, what might be the phenotypes of their children? A. All of their children have hypertrichosis B. All of the sons have hypertrichosis, but none of the daughters C. All of the daughters have hypertrichosis, but none of the sons D. None of their children have hypertrichosis 2. Tube feet of sea stars are used primarily for: A. Reproduction B. Circulation C. Movement D. Sensation Reports Example: Lab Questions: What wavelengths of light worked best for the production of oxygen? Hypothesize why it was those particular wavelengths of light that produced the most oxygen. Why did using the full spectrum of light work best for the production of oxygen? Explain why an increase in carbon dioxide in the Habitation Unit would not result in greater production of oxygen. Your explanation should include a discussion on the light dependent reactions and the Calvin cycle. Repeatable No Methods of Instruction Laboratory Lecture/Discussion Distance Learning Lab: Students will be assigned genotypes and the instructor will inform how those genotypes correspond to particular feeding phenotypes. Candy will then be placed on the tables in front of the students. Students will use their phenotypes to forage for food. Those students that do not collect enough food will be removed from the population. Those students who collect enough food will be allowed to parent the next generation. Using the Mendelian ratios based upon the genotypes of the parents, the instructor will allocate new genotypes to the students previously removed from the game. Gene frequencies will be calculated both before and after each round of play. Lecture: Instructor leads class discussion on the following: "A food manufacturer is advertising a new cake mix as fat-free. Scientists at the US Food and Drug Administration (FDA) are testing the product to see if it truly lacks fat. Hydrolysis of the cake mix yields glucose, fructose, glycerol, a number of amino acids, and several kinds of molecules with long hydrocarbon chains. Further analysis shows that most of these hydrocarbon chains have a carboxyl group (typical to organic acids) at the end. What would you tell the manufacturer if you were the spokesperson for the FDA, and why?" Distance Learning Following a live-recorded lecture on procaryotic and eucaryotic cells, the instructor will guide students through the following process: "Perform an internet search for the websites on cell structure. Find sites that: give an overview and illustrate cell organelles and their functions; compare animal cells and plant cells; compare eukaryotic and prokaryotic cells; and, overall, have descriptions and images that are most helpful in illustrating the content of our chapter After you have found such website(s), post a link to them in our Discussion Board, put a comment on why you think this particular site is helpful and what you liked about it. What additional information did you find there that helped you learn the concepts better?" Typical Out of Class Assignments Reading Assignments 1. Discover something new in science. In the tradition of a "Today I learned" post, read about a new discovery in science. Evaluate what you read and be prepared to discuss the implications for humans and the environment of that work. 2. Review the data collected and results from a scientific experiment provided by the instructor (e.g. science surrounding vaccine acceptance). Evaluate the outcome of the experiment. Identify the hypothesis and variables that were part of that experiment. Writing, Problem Solving or Performance 1. Complete word problems in genetics that are based in genetic terminology. 2. Evaluate the size of the human population on earth today. Use this information to determine the effects that humans have on the natural world. Detail your findings in a two-page essay that demonstrates critical thought. Other (Term projects, research papers, portfolios, etc.) 1. Review the laboratory exercises prior to coming to lab. Answer pre-lab questions prior to arrival in class. 2. Answer review questions posed in lab manual based upon the experiments conducted in lab. 3. Case Studies: Should we clone mammoths? Evaluate what the potential barriers are to cloning mammoths. Discuss the potential effects on the ecosystem of the reintroduction of mammoths into the ecosystem. Use this information to debate issues surrounding the reintroduction of mammoths or other extinct animals back into the ecosystem. Required Materials Concepts of Biology Author: Fowler, Roush, Wise Publisher: Open Stax Publication Date: 2019 Text Edition: Classic Textbook?: OER Link: OER: Campbell Essential Biology Author: Reece, Simon, Dickey Publisher: Benjamin Cummings Publication Date: 2018 Text Edition: 7th Classic Textbook?: OER Link: OER: Laboratory Manual for Biology 11 Author: Carroll, Martinez, Pravosudova Publisher: Sierra College Publication Date: 2015 Text Edition: 4th Classic Textbook?: OER Link: OER: Other materials and-or supplies required of students that contribute to the cost of the course.

Recreation Management

https://catalog.sierracollege.edu/departments/recreation-management/

...Industry STAT C1000 Introduction to Statistics or MATH 0011 Data Science for All or PSYC...