OklahomaOklahoma High School Statistics and Probability
Video lessons and practice for every Statistics and Probability topic. Aligned to Oklahoma Academic Standards Math for high school students.
Oklahoma High School Statistics and Probability | 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). |
Oklahoma High School Statistics and Probability Curriculum
High school Statistics and Probability covers a wide range of skills that help students understand data and make informed decisions. Oklahoma Academic Standards Math outlines what students need to learn, and StudyPug covers every standard with clear video lessons and targeted practice problems.
Data Analysis and Distributions
Students begin by learning to represent data using dot plots, histograms, and box plots. They compare data sets using measures of center — mean and median — and measures of spread such as interquartile range and standard deviation. The course also covers how to identify and interpret outliers and how to fit data to a normal distribution to estimate population percentages.
- Represent data with dot plots, histograms, and box plots
- Compare center and spread across two or more data sets
- Interpret outliers and their effects on data
- Use normal distribution to estimate population percentages
- Summarize categorical data using two-way frequency tables
Scatter Plots, Correlation, and Causation
Students learn to represent two quantitative variables on a scatter plot and use technology to compute the correlation coefficient of a linear fit. A key skill at this level is understanding the difference between correlation and causation — recognizing that a statistical relationship does not prove one variable causes another.
Statistical Inference and Sampling
This section introduces statistics as a process for making inferences about populations from random samples. Students learn the differences among sample surveys, experiments, and observational studies and understand how randomization affects each. They estimate population means and proportions from sample data and develop margins of error using simulation models.
- Understand random sampling and population inference
- Distinguish sample surveys, experiments, and observational studies
- Estimate population means and proportions with margins of error
- Compare two treatments using data from randomized experiments
- Evaluate reports and claims based on data
Probability Rules and Conditional Probability
Students study the rules of probability, including the Addition Rule and the general Multiplication Rule. They explore independent events and conditional probability, learning to calculate P(A given B) and interpret results in real-world contexts. Two-way frequency tables help students decide if events are independent and approximate conditional probabilities.
Random Variables and Expected Value
The course concludes with random variables and probability distributions. Students define random variables, graph probability distributions, and calculate expected values. They develop distributions using both theoretical probabilities and empirical data, and they apply expected value to real decisions — including fair decision-making and strategy analysis using probability concepts.
- Define and graph probability distributions for random variables
- Calculate expected value from theoretical and empirical distributions
- Use permutations and combinations for compound probability problems
- Apply expected value to decisions and strategy analysis
- Use probabilities to evaluate fairness and outcomes