PennsylvaniaPennsylvania High School Statistics Curriculum
Video lessons and practice for every Statistics topic. Aligned to Pennsylvania Core Standards in Math for high school students.
Pennsylvania High School Statistics Curriculum | StudyPugHelp
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). |
Pennsylvania High School Statistics: What Students Learn
High school Statistics in Pennsylvania covers a wide range of skills that help students understand and interpret data in the real world. From creating dot plots and histograms to calculating standard deviation and fitting data to a normal distribution, students develop strong analytical skills throughout the course. StudyPug provides video lessons and practice problems for every one of these topics, aligned to Pennsylvania Core Standards in Math.
Data Analysis and Distributions
Students begin by learning how to represent data visually using dot plots, histograms, and box plots. They compare data sets by examining center (mean and median) and spread (interquartile range and standard deviation). A key skill is interpreting how outliers affect a data set and recognizing when a normal distribution is or is not an appropriate model.
- Create and read dot plots, histograms, and box plots
- Compare data sets using mean, median, IQR, and standard deviation
- Estimate areas under the normal curve using calculators and tables
- Summarize categorical data in two-way frequency tables
Linear Relationships and Scatter Plots
Students represent two quantitative variables on scatter plots and describe the relationship between them. They compute and interpret correlation coefficients using technology and learn the important distinction between correlation and causation — a skill that applies well beyond the statistics classroom.
- Create and interpret scatter plots for two quantitative variables
- Compute correlation coefficients using technology
- Distinguish between correlation and causation
Statistical Inference and Sampling
Students explore how statistics is used to make inferences about populations from random samples. They learn the differences between sample surveys, experiments, and observational studies, and understand how randomization plays a role in each. Using simulation, they estimate population means, develop margins of error, and compare two treatments from randomized experiments.
- Estimate population means and proportions from sample data
- Develop margins of error using simulation models
- Evaluate reports and studies based on data quality and methodology
Probability
The probability unit covers independent events, conditional probability, the Addition Rule, and the Multiplication Rule. Students construct two-way frequency tables as sample spaces and use them to determine independence and calculate conditional probabilities. Permutations and combinations extend their ability to compute probabilities for compound events.
- Determine if events A and B are independent
- Apply the Addition Rule: P(A or B) = P(A) + P(B) − P(A and B)
- Apply the general Multiplication Rule: P(A and B) = P(A)P(B|A)
- 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 distributions using both theoretical and empirical probabilities. These skills connect directly to real-world decision-making, including evaluating fairness and analyzing strategies in contexts like medical testing or game theory.
- Define random variables and graph probability distributions
- Calculate expected value as the mean of a probability distribution
- Weigh outcomes by assigning probabilities to payoff values
- Analyze decisions and strategies using probability concepts