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

Yes. StudyPug covers every Missouri Learning Standards Statistics topic with video lessons and practice problems, so your student can get step-by-step help on any homework question the same night it is assigned.

How long are the video lessons?

Most video lessons run between five and fifteen minutes, focusing on one concept at a time. Your student can pause, rewind, and rewatch as often as needed, making it easy to work at their own pace.

Is there a Missouri state test for High School Statistics?

Missouri uses the MAP assessment, but Statistics is not a separately assessed course at the state level. Your student's school may give its own final exam. StudyPug covers all the Missouri Learning Standards content regardless of the local exam format.

Can my child use StudyPug on a tablet or phone?

Yes. StudyPug works on tablets, phones, and computers, so your student can study at home, at school, or on the go without needing to download a separate app.

Can I try StudyPug before paying?

Yes. StudyPug offers free sample lessons so you can see the content before committing. Every paid plan also comes with a 30-day money-back guarantee, so there is no risk in getting started.

MO High School Statistics Curriculum

Give your student the support they need to keep up with Missouri high school Statistics. Lessons and practice problems follow exactly what local schools teach, from data analysis to probability.

MO 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 Missouri Statistics

Missouri high school Statistics follows the Missouri Learning Standards, covering data analysis, statistical inference, probability, and random variables. Students work through summarizing and comparing data distributions, exploring correlation and regression, using simulation to make inferences, and building a full understanding of probability rules including conditional probability, independence, and expected value. StudyPug provides video lessons and practice problems aligned to every strand in this course.

Strands: Data Analysis, Statistical Inference, Probability, and Random Variables
Video lessons covering every Missouri Learning Standards Statistics topic
Practice problems and step-by-step explanations for each strand
Content aligned to Missouri Learning Standards for high school Statistics

Curriculum topics by strand

Find lessons and practice problems for every strand, aligned to Missouri Learning Standards for high school Statistics.

Topic includes:

Practice

Video

Quiz

Standard

StudyPug Topic

Missouri High School Statistics Topics

Data Distributions: Represent data with dot plots, histograms, and box plots; compare center and spread using median, mean, interquartile range, and standard deviation; interpret shape differences and outlier effects.
Normal Distribution and Two-Way Tables: Fit data to a normal distribution using mean and standard deviation; estimate population percentages; summarize categorical data in two-way frequency tables and interpret joint, marginal, and conditional relative frequencies.
Scatter Plots, Correlation, and Causation: Represent two quantitative variables on a scatter plot; compute and interpret the correlation coefficient of a linear fit; distinguish between correlation and causation.
Statistical Inference and Sampling: Understand statistics as an inference process; evaluate sample surveys, experiments, and observational studies; estimate population means and proportions; develop margins of error through simulation; evaluate data-based reports.
Probability Rules: Apply the Addition Rule and the general Multiplication Rule; understand conditional probability and independence; construct and interpret two-way frequency tables as sample spaces.
Random Variables and Expected Value: Define random variables; graph probability distributions; calculate expected value; weigh outcomes of decisions; analyze decisions and strategies using probability concepts.

How StudyPug Helps Missouri High School Statistics Students

When a student gets stuck on a concept like the normal distribution or conditional probability, they can go straight to the matching video lesson, watch a worked example, and then try practice problems with immediate feedback. This keeps learning moving forward rather than waiting for the next class period.

StudyPug lets students work through each Missouri Learning Standards Statistics strand at their own pace, revisiting any lesson as many times as needed until the concept clicks.

Aligned to Missouri High School Statistics Curriculum

Every lesson and practice problem on StudyPug is built around the Missouri Learning Standards for high school Statistics, covering data analysis, inference, probability, and random variables - exactly what Missouri students are expected to learn in this course.

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Written by the StudyPug Math Team

Last updated June 5, 2026

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