ArkansasArkansas High School Statistics Curriculum
Video lessons and practice for every high school Statistics topic. Aligned to Arkansas Mathematics Standards so students can keep up with class or get ahead.
Arkansas 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). |
Arkansas High School Statistics: What Students Learn
High school Statistics in Arkansas covers a wide range of skills that help students understand and interpret data in the real world. The course is aligned to Arkansas Mathematics Standards and prepares students for college-level math, the ACT, and data-driven careers.
Data Analysis and Distributions
Students start by learning how to represent data using dot plots, histograms, and box plots. They compare data sets using measures of center — like mean and median — and measures of spread, including interquartile range and standard deviation. Understanding how outliers affect data is a key part of this unit.
- Dot plots, histograms, and box plots
- Mean, median, and standard deviation
- Interquartile range and outliers
- Normal distribution and area under the curve
Categorical Data and Two-Way Tables
Students learn to organize categorical data into two-way frequency tables and interpret joint, marginal, and conditional relative frequencies. This unit builds skills in identifying associations and trends between two categories.
Scatter Plots, Correlation, and Causation
This unit focuses on representing two quantitative variables on a scatter plot, computing the correlation coefficient using technology, and understanding the difference between correlation and causation. Students learn that a strong correlation does not mean one variable causes the other.
Statistical Inference and Sampling
Students explore how statistics is used to make inferences about populations from random samples. Topics include sample surveys, experiments, observational studies, margins of error, and simulation. Students also evaluate real-world data reports and determine whether conclusions are supported by the data.
- Random sampling and population parameters
- Sample surveys vs. experiments vs. observational studies
- Margin of error through simulation
- Evaluating data reports
Probability
The probability unit covers independent and dependent events, conditional probability, the Addition Rule, the Multiplication Rule, permutations, and combinations. Students apply these concepts to compound events and solve real-world problems.
- Independent events and conditional probability
- Two-way tables as sample spaces
- Addition Rule: P(A or B) = P(A) + P(B) − P(A and B)
- Multiplication Rule: P(A and B) = P(A)P(B|A)
- Permutations and combinations
Random Variables and Expected Value
Students define random variables, graph probability distributions, and calculate expected value. They develop probability distributions using both theoretical and empirical methods, and apply expected value to decision-making scenarios such as product testing and medical testing.