Will this help with my child's High School Statistics homework?

Yes. StudyPug covers every strand in Kansas high school Statistics, from reading histograms and box plots to calculating conditional probabilities and expected values, so students can get targeted help on exactly the topic causing trouble.

How long are the video lessons for High School Statistics?

Most video lessons run between a few minutes and around ten minutes, focusing on one concept at a time. Students can pause, rewind, and re-watch as many times as they need, which is useful for topics like normal distributions or the Multiplication Rule.

Is there a Kansas state test for High School Statistics?

Kansas high school Statistics is not a separately assessed course on the KAP. Students who take Statistics as part of their high school sequence may encounter data and probability content on general math assessments, but there is no standalone Statistics exam at this level.

Can my child use StudyPug on a tablet or phone?

Yes. StudyPug works on tablets, phones, and desktop computers, so students can review scatter plots or work through probability problems at home, at school, or on the go without needing a specific device.

Can I try StudyPug before paying?

Yes. StudyPug offers free sample lessons so you can see how the content works before committing. A 30-day money-back guarantee is also included, giving your family time to decide if it is the right fit.

KS High School Statistics Curriculum

Give your high schooler the support they need to succeed in Kansas Statistics. Our lessons follow the Kansas Standards, covering data analysis, probability, and statistical inference from the ground up.

KS High School Statistics Curriculum

IDStandardStudyPug Topic

CC.HSS.ID.A.1Represent data with plots on the real number line (dot plots, histograms, and box plots).
- Why learn log?
- Equation of the best fit line
- The determinant of a 2 x 2 matrix
- Frequency distribution and histograms
CC.HSS.ID.A.2Use 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.
- Median and mode
- Mean
- Range and outliers
- Center of a data set: mean, median, mode
- Spread of a data set - standard deviation & variance
CC.HSS.ID.A.3Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).
- Application of averages
- Shapes of distributions
CC.HSS.ID.A.4Use 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.
- Introduction to normal distribution
- Normal distribution and continuous random variable
- Z-scores and random continuous variables
CC.HSS.ID.B.5Summarize 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.
- Reading and drawing Venn diagrams
- Probability with Venn diagrams
CC.HSS.ID.B.6Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.
- Reading and drawing line graphs
- Bivariate, scatter plots and correlation
CC.HSS.IC.A.1Understand statistics as a process for making inferences about population parameters based on a random sample from that population.
- Sampling methods
CC.HSS.IC.A.2Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation.
- Sampling distributions
- Rare event rule
CC.HSS.IC.B.3Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.
- Census and bias
CC.HSS.IC.B.4Use 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.
- Margin of error
- Confidence intervals to estimate population mean
- Making a confidence interval
CC.HSS.IC.B.5Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant.
- Traditional hypothesis testing
- P-value hypothesis testing
- Analysis of variance (ANOVA)
CC.HSS.IC.B.6Evaluate reports based on data.
- Influencing factors in data collection
CC.HSS.CP.A.2Understand 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.
- Probability of independent events
- Multiplication rule for
- Probability of independent events
CC.HSS.CP.A.3Understand 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.
- Conditional probability
CC.HSS.CP.A.5Recognize and explain the concepts of conditional probability and independence in everyday language and everyday situations.
- Comparing experimental and theoretical probability
CC.HSS.CP.B.7Apply the Addition Rule, P(A or B) = P(A) + P(B) - P(A and B), and interpret the answer in terms of the model.
- Addition rule for
CC.HSS.CP.B.9Use permutations and combinations to compute probabilities of compound events and solve problems.
- Permutations
- Combinations
- Probability involving permutations and combinations
CC.HSS.MD.A.1Define 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.
- Probability distribution - histogram, mean, variance & standard deviation
CC.HSS.MD.A.2Calculate the expected value of a random variable; interpret it as the mean of the probability distribution.
- Properties of expectation
CC.HSS.MD.A.3Develop a probability distribution for a random variable defined for a sample space in which theoretical probabilities can be calculated; find the expected value.
- Binomial distribution
- Mean and standard deviation of binomial distribution
CC.HSS.MD.B.7Analyze decisions and strategies using probability concepts (e.g., product testing, medical testing, pulling a hockey goalie at the end of a game).
- Type 1 and type 2 errors

High School Statistics

About High School Kansas Statistics

Kansas high school Statistics follows the Kansas Standards, organized around interpreting data, modeling with probability, and drawing statistical inferences. Students work through data representation and distribution analysis, exploring center and spread across data sets, two-way frequency tables, scatter plots, correlation, and the distinction between correlation and causation. The course also covers probability rules, conditional probability, random variables, expected value, and using simulations and experiments to make inferences about populations. StudyPug provides step-by-step lessons and practice problems matched to every strand in this course.

Strands covered: data representation, comparing distributions, normal distributions, two-way tables, scatter plots and correlation, probability rules, conditional probability, random variables and expected value, and statistical inference
Video lessons walking through every Statistics concept, from dot plots to the Multiplication Rule
Practice problems and worked examples for each strand, so students can check understanding and prepare for assessments
Content aligned to Kansas Standards for high school Statistics

Curriculum topics by strand

Lessons and practice for every strand, aligned to the Kansas Standards for high school Statistics.

Topic includes:

Practice

Video

Quiz

Standard

StudyPug Topic

Kansas High School Statistics Topics

Data representation: Displaying data with dot plots, histograms, and box plots on the real number line.
Comparing distributions: Using center (mean, median) and spread (interquartile range, standard deviation) to compare two or more data sets, and interpreting differences in shape, center, and spread including the effects of outliers.
Normal distributions: Fitting a data set to a normal distribution using the mean and standard deviation, and estimating population percentages and areas under the normal curve.
Two-way frequency tables: Summarizing categorical data for two categories and interpreting joint, marginal, and conditional relative frequencies to recognize associations and trends.
Scatter plots and correlation: Representing two quantitative variables on a scatter plot, computing and interpreting the correlation coefficient, and distinguishing between correlation and causation.
Statistical inference: Understanding statistics as a process for making inferences from random samples, using sample surveys, experiments, and observational studies, estimating population means and proportions with margins of error, and evaluating data-based reports.
Probability rules: Independence, the Addition Rule, and the general Multiplication Rule in a uniform probability model.
Conditional probability: Computing and interpreting conditional probabilities, constructing two-way frequency tables as sample spaces, and recognizing independence in everyday situations.
Permutations and combinations: Using counting methods to compute probabilities of compound events.
Random variables and expected value: Defining random variables, graphing probability distributions, calculating expected values, and using expected values to weigh outcomes and analyze decisions.

How StudyPug Helps Kansas High School Statistics Students

When a student gets stuck on a Statistics problem - whether it is interpreting a two-way table, applying the Multiplication Rule, or deciding whether two events are independent - StudyPug lets them jump directly to the relevant lesson and work through a clear, step-by-step explanation at their own pace. Practice problems with full solutions follow each lesson so students can confirm they understand the concept before moving on.

The course structure mirrors the Kansas Standards, so students always know which strand they are in and can easily find topics that match what their class is covering that week. Whether preparing for a unit test on normal distributions or reviewing scatter plots and correlation, the content is organized to make targeted review straightforward.

Aligned to Kansas High School Statistics Curriculum

Every lesson and practice problem in StudyPug's high school Statistics course is built around the Kansas Standards, covering the full range of strands that Kansas students are expected to master - from data representation and probability rules through statistical inference and decision analysis. Families can trust that the content students practice on StudyPug is the content their Kansas teacher is responsible for teaching.

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Jump into practice questions for every KS High School Statistics topic - with instant feedback and step-by-step video solutions when you get stuck.

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Written by the StudyPug Math Team

Last updated June 5, 2026

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