Will this help with my child's high school statistics homework?

Yes. StudyPug covers every Utah Core Standards statistics topic, including data distributions, scatter plots, probability rules, and inference, with step-by-step video lessons and practice problems matched to what is taught in class.

How long are the video lessons for high school statistics?

Most video lessons run between five and fifteen minutes, so students can watch one focused lesson when they get stuck on a specific topic such as the normal distribution, correlation coefficients, or conditional probability, without sitting through a full lecture.

Is there a Utah state test for high school statistics?

Utah administers the Aspire Plus assessment, but it targets specific grade levels rather than every high school course. Whether this statistics course falls in an assessed year depends on your student's grade - check with your school for the current testing schedule.

Can my child use StudyPug on a tablet or phone?

Yes. StudyPug works on tablets, phones, and computers, so students can review a lesson on normal distributions or work through probability practice problems at home, in the library, or on the go.

Can I try StudyPug before paying?

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

UT High School Statistics Curriculum

Give your high schooler step-by-step support for every Utah Core Standards statistics topic - from analyzing data distributions to probability and making inferences from random samples.

UT 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

Introductory Statistics

About High School Utah statistics

Utah follows the Utah Core Standards, organizing high school statistics around interpreting data, drawing conclusions from probability models, and making statistical inferences. This course covers data representation and distribution analysis, correlation and scatter plots, two-way frequency tables, probability rules and random variables, and simulation-based inference. StudyPug provides video lessons, practice problems, and step-by-step explanations aligned to every Utah Core Standards strand.

Data analysis, probability, and statistical inference strands aligned to Utah Core Standards
Video lessons covering distributions, scatter plots, conditional probability, and random variables
Practice problems and worked examples for every topic from normal curves to permutations
Content matched to Utah Core Standards for high school Introductory Statistics

Curriculum topics by strand

Lessons and practice for every strand, aligned to the Utah Core Standards for high school Introductory Statistics.

Topic includes:

Practice

Video

Quiz

Standard

StudyPug Topic

UT High School Statistics Topics

Data Representation and Distribution: Dot plots, histograms, and box plots; comparing center and spread using mean, median, interquartile range, and standard deviation; interpreting shape, outliers, and the normal distribution.
Categorical and Bivariate Data: Two-way frequency tables with joint, marginal, and conditional relative frequencies; scatter plots; correlation coefficients; distinguishing correlation from causation.
Statistical Inference and Sampling: Inferences about population parameters from random samples; sample surveys, experiments, and observational studies; margin of error through simulation; evaluating data-based reports.
Probability Foundations: Independent events; conditional probability and the formula P(A and B)/P(B); the Addition Rule and the general Multiplication Rule; two-way tables as sample spaces.
Counting and Compound Events: Permutations and combinations; computing probabilities of compound events.
Random Variables and Expected Value: Defining random variables; probability distributions; expected value from theoretical and empirical distributions; using expected value to weigh decisions and analyze strategies.

How StudyPug Helps Utah High School Statistics Students

When a student gets stuck on a concept like the normal curve or conditional probability, StudyPug lets them go back to exactly the lesson they need. Each topic is broken into short video lessons followed by practice problems with step-by-step solutions, so students can work through the material at their own pace and build confidence before the next class.

Parents can track progress across every Utah Core Standards strand, making it easy to spot gaps in understanding - whether that is reading a scatter plot, applying the Multiplication Rule, or interpreting a margin of error - and address them before they affect a grade.

Aligned to Utah High School Statistics Curriculum

Every lesson and practice problem in StudyPug's Introductory Statistics course is built around the Utah Core Standards, covering the same data analysis, probability, and inference topics that Utah high school students encounter in class, so there are no surprises and no wasted study time.

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Practice questions for every UT 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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