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West Virginia High School Statistics Curriculum

Video lessons and practice for every high school Statistics topic. Aligned to WV College Career Ready Standards Math so West Virginia students can keep up or get ahead.

West Virginia High School Statistics Curriculum | StudyPugHelp

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ID

Standard

StudyPug Topic

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.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.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.CP.A.3

Understand the conditional probability of A given B as P(A and B)/P(B), and interpret independence of A and B as saying that the conditional probability of A given B is the same as the probability of A, and the conditional probability of B given A is the same as the probability of B.

CC.HSS.CP.A.5

Recognize and explain the concepts of conditional probability and independence in everyday language and everyday situations.

CC.HSS.CP.B.7

Apply the Addition Rule, P(A or B) = P(A) + P(B) - P(A and B), and interpret the answer in terms of the model.

CC.HSS.CP.B.9

Use permutations and combinations to compute probabilities of compound events and solve problems.

CC.HSS.MD.A.1

Define a random variable for a quantity of interest by assigning a numerical value to each event in a sample space; graph the corresponding probability distribution using the same graphical displays as for data distributions.

CC.HSS.MD.A.2

Calculate the expected value of a random variable; interpret it as the mean of the probability distribution.

CC.HSS.MD.A.3

Develop a probability distribution for a random variable defined for a sample space in which theoretical probabilities can be calculated; find the expected value.

CC.HSS.MD.B.7

Analyze decisions and strategies using probability concepts (e.g., product testing, medical testing, pulling a hockey goalie at the end of a game).

High School Statistics in West Virginia

West Virginia high school Statistics follows the WV College Career Ready Standards Math. The course is divided into three major areas: interpreting data, understanding probability, and making statistical inferences. StudyPug covers every standard in this course with video lessons and practice problems students can access anytime.

Data Analysis and Distributions

Students begin by learning how to represent and interpret data. Topics include dot plots, histograms, and box plots. Students compare data sets using measures of center such as mean and median, and measures of spread such as interquartile range and standard deviation. The normal distribution is introduced, and students learn to estimate population percentages using calculators, spreadsheets, and tables.

  • Represent data with dot plots, histograms, and box plots
  • Compare center and spread across two or more data sets
  • Identify the effect of outliers on shape, center, and spread
  • Fit a data set to a normal distribution and estimate population percentages

Scatter Plots, Correlation, and Causation

Students plot two quantitative variables on a scatter plot and describe the relationship between them. They compute and interpret the correlation coefficient of a linear fit using technology, then learn the critical distinction between correlation and causation.

  • Represent bivariate data on a scatter plot
  • Compute and interpret the correlation coefficient using technology
  • Distinguish between correlation and causation

Statistical Inference and Sampling

This section introduces statistics as a process for drawing conclusions about populations from random samples. Students work with sample surveys, experiments, and observational studies. They develop margins of error using simulation models and evaluate data reports critically.

  • Understand inference as a process using random samples
  • Recognize differences among surveys, experiments, and observational studies
  • Estimate population means and proportions from sample data
  • Use simulation to compare two treatments and evaluate significance
  • Evaluate reports based on data for validity and bias

Probability

Students develop a solid foundation in probability, including independent events, conditional probability, and the Addition and Multiplication Rules. They construct and interpret two-way frequency tables and apply probability concepts to real-world situations.

  • Determine independence using the product rule for probabilities
  • Calculate conditional probability using P(A and B)/P(B)
  • Construct and interpret two-way frequency tables
  • Apply the Addition Rule and general Multiplication Rule
  • Use permutations and combinations for compound event probabilities

Random Variables and Expected Value

Students define random variables, graph probability distributions, and calculate expected values. They develop probability distributions from both theoretical and empirical data and apply expected value concepts to real decisions.

  • Define random variables and graph probability distributions
  • Calculate and interpret expected value as the mean of a distribution
  • Develop distributions from theoretical and empirical probabilities
  • Weigh outcomes by assigning probabilities to payoff values
  • Analyze decisions and strategies using probability concepts