IllinoisIllinois High School Statistics Curriculum
Video lessons and practice for every high school Statistics topic. Aligned to Illinois Learning Standards for Math so students are ready for class and exams.
Illinois 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). |
Illinois High School Statistics: What Students Learn
Illinois high school Statistics follows the Illinois Learning Standards for Math, covering a wide range of topics from exploratory data analysis to probability and statistical inference. Students learn to represent data with dot plots, histograms, and box plots, then progress to comparing data sets using mean, median, standard deviation, and interquartile range.
Data Analysis and Distributions
Students interpret differences in shape, center, and spread across data sets and learn how outliers affect analysis. They use the mean and standard deviation to fit data to a normal distribution and estimate population percentages using the normal curve. Two-way frequency tables help students summarize categorical data and recognize associations between variables.
- Dot plots, histograms, and box plots
- Mean, median, standard deviation, and IQR
- Normal distribution and population estimates
- Two-way frequency tables and relative frequencies
Scatter Plots, Correlation, and Causation
Students represent two quantitative variables on a scatter plot, compute the correlation coefficient using technology, and interpret linear fits. A key concept is distinguishing between correlation and causation — a skill that applies far beyond the classroom.
Statistical Inference and Sampling
This unit covers the logic behind using random samples to make inferences about populations. Students learn the differences among sample surveys, experiments, and observational studies. They use simulation models to develop margins of error, compare treatments from randomized experiments, and evaluate data-based reports critically.
- Random sampling and population inference
- Sample surveys vs. experiments vs. observational studies
- Margin of error through simulation
- Evaluating data reports
Probability: Rules, Tables, and Independence
Students build a strong foundation in probability, starting with independent events and conditional probability. They construct two-way frequency tables as sample spaces, apply the Addition Rule and the general Multiplication Rule, and use permutations and combinations to find probabilities of compound events.
Random Variables and Expected Value
In the final unit, students define random variables, graph probability distributions, and calculate expected values. They develop probability distributions both theoretically and empirically. These concepts connect directly to real-world decision-making, from product testing to medical testing to sports strategy.
StudyPug covers every one of these Illinois Learning Standards topics with video lessons and practice problems so students can get homework help, prepare for exams, or review concepts at their own pace.