LouisianaLouisiana High School Statistics and Probability Curriculum
Video lessons and practice for every Statistics and Probability topic. Aligned to Louisiana Student Standards Math for high school students.
Louisiana Statistics and Probability 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). |
Louisiana High School Statistics and Probability
Statistics and Probability is a foundational high school math course in Louisiana. It teaches students how to collect, analyze, and interpret data — skills that apply to science, business, and everyday decision-making. StudyPug covers every topic in this course with clear video lessons and practice problems aligned to Louisiana Student Standards Math.
Data Analysis and Distributions
Students start by learning how to represent data using dot plots, histograms, and box plots. From there, they explore measures of center and spread, including mean, median, interquartile range, and standard deviation. The course also covers how to fit data to a normal distribution and estimate population percentages using calculators and tables.
- Dot plots, histograms, and box plots
- Mean, median, IQR, and standard deviation
- Normal distribution and area under the curve
- Outliers and their effect on data shape
Bivariate Data and Correlation
Students learn to represent two quantitative variables on scatter plots and describe relationships between them. They compute and interpret correlation coefficients using technology and learn the critical difference between correlation and causation.
- Scatter plots and linear fit
- Correlation coefficient interpretation
- Correlation vs. causation
- Two-way frequency tables and relative frequencies
Statistical Inference and Sampling
This section introduces statistics as a process for making inferences about populations from random samples. Students explore sample surveys, experiments, and observational studies. They use simulation to estimate margins of error and evaluate the significance of differences between treatments.
- Random sampling and population estimates
- Margin of error through simulation
- Randomized experiments and treatment comparisons
- Evaluating data reports
Probability Rules and Conditional Probability
Students build a strong foundation in probability, including independent events, conditional probability, the Addition Rule, and the Multiplication Rule. Two-way frequency tables are used as sample spaces to calculate and interpret probabilities in real-world contexts.
- Independent events and P(A and B)
- Conditional probability: P(A|B)
- Addition Rule and Multiplication Rule
- Permutations and combinations for compound events
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 apply these concepts to real decisions, including fair games, product testing, and medical testing.
- Defining and graphing random variables
- Theoretical and empirical probability distributions
- Expected value and decision-making
- Analyzing strategies using probability