West VirginiaData Science
West Virginia High School Data Science Curriculum
Video lessons and practice for every Data Science topic. Aligned to WV College Career Ready Standards Math for West Virginia high school students.
West Virginia High School Data Science | StudyPugHelp
ID | Standard | StudyPug Topic |
|---|---|---|
CC.HSN.Q.A.1 | Use units as a way to understand problems and to guide the solution of multi-step problems; choose and interpret units consistently in formulas; choose and interpret the scale and the origin in graphs and data displays. |
CC.HSN.Q.A.2 | Define appropriate quantities for the purpose of descriptive modeling. |
CC.HSN.Q.A.3 | Choose a level of accuracy appropriate to limitations on measurement when reporting quantities. |
CC.HSA.SSE.A.1 | Interpret expressions that represent a quantity in terms of its context. |
CC.HSA.CED.A.1 | Create equations and inequalities in one variable and use them to solve problems. Include equations arising from linear and quadratic functions, and simple rational and exponential functions. |
CC.HSA.CED.A.2 | Create equations in two or more variables to represent relationships between quantities; graph equations on coordinate axes with labels and scales. |
CC.HSA.REI.D.11 | Explain why the x-coordinates of the points where the graphs of the equations y = f(x) and y = g(x) intersect are the solutions of the equation f(x) = g(x); find the solutions approximately, e.g., using technology to graph the functions, make tables of values, or find successive approximations. Include cases where f(x) and/or g(x) are linear, polynomial, rational, absolute value, exponential, and logarithmic functions. |
CC.HSF.IF.A.2 | Use function notation, evaluate functions for inputs in their domains, and interpret statements that use function notation in terms of a context. |
CC.HSF.IF.B.4 | For a function that models a relationship between two quantities, interpret key features of graphs and tables in terms of the quantities, and sketch graphs showing key features given a verbal description of the relationship. |
CC.HSF.IF.B.6 | Calculate and interpret the average rate of change of a function (presented symbolically or as a table) over a specified interval. Estimate the rate of change from a graph. |
CC.HSF.BF.A.1 | Write a function that describes a relationship between two quantities. |
CC.HSF.LE.A.1 | Distinguish between situations that can be modeled with linear functions and with exponential functions. |
CC.HSF.LE.B.5 | Interpret the parameters in a linear or exponential function in terms of a context. |
CC.HSS.ID.A.1 | Represent data with plots on the real number line (dot plots, histograms, and box plots). |
CC.HSS.ID.A.2 | Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets. |
CC.HSS.ID.A.3 | Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers). |
CC.HSS.ID.A.4 | Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve. |
CC.HSS.ID.B.5 | Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data. |
CC.HSS.ID.B.6 | Represent data on two quantitative variables on a scatter plot, and describe how the variables are related. |
CC.HSS.ID.C.7 | Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data. |
CC.HSS.IC.A.1 | Understand statistics as a process for making inferences about population parameters based on a random sample from that population. |
CC.HSS.IC.A.2 | Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation. |
CC.HSS.IC.B.3 | Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each. |
CC.HSS.IC.B.4 | Use data from a sample survey to estimate a population mean or proportion; develop a margin of error through the use of simulation models for random sampling. |
CC.HSS.IC.B.5 | Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant. |
CC.HSS.IC.B.6 | Evaluate reports based on data. |
CC.HSS.CP.A.1 | Describe events as subsets of a sample space (the set of outcomes) using characteristics (or categories) of the outcomes, or as unions, intersections, or complements of other events ("or," "and," "not"). |
CC.HSS.CP.A.2 | Understand that two events A and B are independent if the probability of A and B occurring together is the product of their probabilities, and use this characterization to determine if they are independent. |
CC.HSS.MD.A.2 | Calculate the expected value of a random variable; interpret it as the mean of the probability distribution. |
West Virginia High School Data Science Curriculum
Data Science is a high school math course in West Virginia that combines statistics, algebra, and data reasoning. Students learn to collect, display, and interpret data while building skills in probability and mathematical modeling. StudyPug covers every topic in the course with video lessons and practice problems aligned to the WV College Career Ready Standards Math.
Key Topics in WV High School Data Science
- Using units to understand and guide multi-step problem solving
- Creating equations and inequalities in one or more variables
- Interpreting functions and their key features from graphs and tables
- Calculating and interpreting average rate of change
- Representing data with dot plots, histograms, and box plots
- Comparing data sets using mean, median, standard deviation, and IQR
- Fitting data to a normal distribution and estimating population percentages
- Analyzing two-way frequency tables for categorical data
- Interpreting slope and intercept of linear models in context
- Computing and interpreting correlation coefficients using technology
- Distinguishing between correlation and causation
- Understanding sampling, simulation, and statistical inference
- Evaluating reports based on data
- Calculating expected value of a random variable
How StudyPug Supports WV Data Science Students
Each StudyPug lesson breaks a standard into a short, clear video explanation followed by practice problems. Students can search by topic, rewatch lessons, and work through examples at their own speed. This makes it easy to catch up after missing class or to get ahead before a test.
StudyPug is designed for real homework situations. If your student is stuck on interpreting a scatter plot or figuring out whether two events are independent, they can find that exact topic and get a clear explanation right away.
Aligned to WV College Career Ready Standards Math
Every lesson in StudyPug's Data Science course is mapped to the WV College Career Ready Standards Math. West Virginia high school students can use StudyPug alongside their regular class to reinforce what they are learning and prepare for assessments and college-level coursework.