NevadaNevada High School Statistics Curriculum
Video lessons and practice for every high school Statistics topic. Aligned to Nevada Academic Content Standards Math so students can keep up with class or get ahead.
Nevada 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). |
Nevada High School Statistics: What Students Learn
High school Statistics in Nevada gives students the tools to collect, analyze, and interpret data. The course covers everything from reading histograms and box plots to understanding the normal distribution and making inferences about populations. StudyPug has video lessons and practice problems for every topic, aligned to Nevada Academic Content Standards Math.
Data Analysis and Distributions
Students start by learning how to represent data using dot plots, histograms, and box plots. From there, they compare data sets using measures of center like mean and median, and measures of spread like interquartile range and standard deviation. They also learn how to identify outliers and interpret what those outliers mean in context.
- Representing data with dot plots, histograms, and box plots
- Comparing center and spread across two or more data sets
- Fitting data to a normal distribution and estimating population percentages
- Interpreting two-way frequency tables with joint, marginal, and conditional relative frequencies
Scatter Plots, Correlation, and Causation
Students learn to plot two quantitative variables on a scatter plot and describe relationships between them. They compute the correlation coefficient using technology and interpret what it means. A key lesson is understanding the difference between correlation and causation — just because two variables are related does not mean one causes the other.
Statistical Inference and Study Design
This section teaches students how statistics is used to draw conclusions about populations from samples. Students learn the difference between sample surveys, experiments, and observational studies, and how randomization affects each. They use simulation to estimate margins of error and evaluate whether differences between groups are statistically significant.
- Estimating population means and proportions from sample data
- Developing margin of error using simulation models
- Comparing two treatments using randomized experiments
- Evaluating reports and data-based claims critically
Probability and Conditional Probability
Students explore foundational probability concepts including independent events, conditional probability, and the rules for combining probabilities. They use two-way tables to approximate conditional probabilities and apply the Addition Rule and Multiplication Rule in real-world models.
- Understanding independence: P(A and B) = P(A) × P(B)
- Conditional probability: P(A|B) = P(A and B)/P(B)
- Addition Rule: P(A or B) = P(A) + P(B) − P(A and B)
- Permutations and combinations for compound event probabilities
Random Variables and Expected Value
Students define random variables, graph probability distributions, and calculate expected values. They develop probability distributions from both theoretical models and empirical data. Expected value is applied to real decisions — from product testing to analyzing strategies in games and medical scenarios.