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

Yes. StudyPug covers every strand in Tennessee high school Statistics, from data distributions and scatter plots to probability models and inference, so students can find help on the exact topic they are stuck on.

How long are the video lessons for High School Statistics?

Lessons are designed to be short and focused, typically covering one concept at a time. Students can pause, rewind, and rewatch any lesson as many times as they need before moving on to practice problems.

Is there a Tennessee state test for High School Statistics?

Tennessee uses the TCAP assessment program, but Statistics is an elective course and is not a standalone TCAP tested course. Students in tested grades and courses should check their school for specific assessment requirements.

Can my child use StudyPug on a tablet or phone?

Yes. StudyPug works on tablets, phones, and computers, so students can access Statistics lessons and practice problems at home, at school, or on the go whenever they need support.

Can I try StudyPug before paying?

Yes. StudyPug offers free sample lessons so families can explore the content before subscribing. There is also a 30-day money-back guarantee, so you can sign up with confidence.

TN High School Statistics Curriculum

Give your teen the support they need to succeed in Tennessee high school Statistics. Our lessons and practice problems follow the Tennessee Academic Standards, covering data analysis, probability, and inference.

TN 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 Tennessee Statistics

Tennessee high school Statistics follows the Tennessee Academic Standards, structured around interpreting data distributions, probability, and statistical inference. Students work through analyzing and comparing data sets, fitting normal distributions, exploring correlation and causation, designing studies, and building probability models including conditional probability, random variables, and expected value. StudyPug provides video lessons and step-by-step practice problems aligned to every strand in this course.

Data analysis, probability, statistical inference, and random variables
Video lessons for every Tennessee Academic Standards Statistics topic
Practice problems and worked examples for each strand
Aligned to Tennessee Academic Standards for high school Statistics

Curriculum topics by strand

Lessons and practice problems for every strand, aligned to the Tennessee Academic Standards for high school Statistics.

Topic includes:

Practice

Video

Quiz

Standard

StudyPug Topic

TN High School Statistics Topics

Data distributions: Representing data with dot plots, histograms, and box plots; comparing center and spread using median, mean, interquartile range, and standard deviation; interpreting shape, outliers, and the normal distribution.
Categorical and bivariate data: Summarizing categorical data in two-way frequency tables with joint, marginal, and conditional relative frequencies; representing two quantitative variables on scatter plots and describing relationships.
Correlation and linear models: Computing and interpreting the correlation coefficient of a linear fit; distinguishing between correlation and causation.
Statistical inference and study design: Understanding statistics as inference from random samples; comparing sample surveys, experiments, and observational studies; estimating population means and proportions with margins of error; evaluating reports based on data.
Probability: Independent and conditional probability; two-way frequency tables as sample spaces; the Addition Rule and general Multiplication Rule; permutations and combinations for compound events.
Random variables and expected value: Defining random variables; graphing probability distributions; calculating and interpreting expected value; weighing decisions and analyzing strategies using probability concepts.

How StudyPug Helps Tennessee High School Statistics Students

When a student gets stuck on a concept like the normal distribution or conditional probability, StudyPug lets them go back to a focused video lesson and work through practice problems at their own pace. Step-by-step explanations break down each strand so students build understanding before moving on.

From interpreting scatter plots to applying the Multiplication Rule, every topic in the Tennessee Academic Standards for Statistics is covered with worked examples and guided practice designed to mirror what students see in class.

Aligned to Tennessee High School Statistics Curriculum

All StudyPug Statistics content is aligned to the Tennessee Academic Standards for high school Statistics, so every lesson on data analysis, probability, inference, and random variables connects directly to what students are taught in Tennessee classrooms.

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Written by the StudyPug Math Team

Last updated June 5, 2026

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