MaineMaine High School Statistics Curriculum
Video lessons and practice for every high school Statistics topic. Aligned to Maine Learning Results Math standards. Get help with data, probability, and more.
Maine 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). |
Maine High School Statistics: What Students Learn
High school Statistics in Maine introduces students to the tools and reasoning needed to collect, analyze, and interpret data. Aligned to Maine Learning Results Math standards, this course covers everything from reading dot plots and histograms to understanding the normal distribution and making inferences about populations.
Data Analysis and Distributions
Students begin by learning how to represent data using dot plots, histograms, and box plots. They compare data sets using measures of center — such as mean and median — and measures of spread, including interquartile range and standard deviation. Students also learn to identify outliers and explain how extreme values affect the shape and spread of a distribution.
- Dot plots, histograms, and box plots
- Mean, median, and standard deviation
- Interpreting shape, center, and spread
- Normal distribution and estimating population percentages
- Two-way frequency tables and relative frequencies
Bivariate Data and Correlation
Students explore relationships between two quantitative variables using scatter plots. They compute and interpret correlation coefficients, fit linear models to data, and learn the critical distinction between correlation and causation.
- Scatter plots and linear models
- Correlation coefficient interpretation
- Correlation vs. causation
Statistical Inference and Sampling
This section covers the logic of using sample data to draw conclusions about populations. Maine students learn the differences among sample surveys, experiments, and observational studies. They use simulation to estimate margins of error and evaluate whether differences between groups are statistically significant.
- Random sampling and population inference
- Sample surveys, experiments, and observational studies
- Margin of error through simulation
- Randomized experiments and significance
- Evaluating data-based reports
Probability
Students develop a solid foundation in probability, including independent and conditional probability, the Addition Rule, and the Multiplication Rule. They work with two-way tables to approximate conditional probabilities and solve real-world problems using permutations and combinations.
- Independent and conditional probability
- Addition Rule and Multiplication Rule
- Two-way tables as sample spaces
- Permutations and combinations
Random Variables and Expected Value
The final topics introduce random variables and probability distributions. Students calculate expected values, develop both theoretical and empirical probability distributions, and apply expected value to decision-making and fairness problems.
- Defining random variables and probability distributions
- Expected value calculation and interpretation
- Theoretical vs. empirical probability distributions
- Using probability to make fair decisions
- Analyzing decisions using probability concepts
How StudyPug Helps Maine Statistics Students
StudyPug provides video lessons and practice problems for every topic in Maine's high school Statistics course. Whether a student needs help understanding the normal distribution, interpreting a correlation coefficient, or working through a conditional probability problem, they can find a lesson, watch the explanation, and practice right away. Every topic is aligned to Maine Learning Results Math standards.