MA.912.S: Statistics

MA.912.S.1: Learn to define appropriate questions for research, and to pose questions in a form that can be answered by collecting and analyzing data.

MA.912.S.1.1: Formulate an appropriate research question to be answered by collecting data or performing an experiment.

 Correlation
 Describing Data Using Statistics
 Real-Time Histogram

MA.912.S.1.2: Determine appropriate and consistent standards of measurement for the data to be collected in a survey or experiment.

 Polling: City
 Polling: Neighborhood
 Populations and Samples

MA.912.S.2: Learn key methods for collecting data and basic sampling principles.

MA.912.S.2.1: Compare the difference between surveys, experiments, and observational studies, and what types of questions can and cannot be answered by a particular design.

 Correlation

MA.912.S.2.2: Apply the definition of random sample and basic types of sampling, including representative samples, stratified samples, censuses.

 Polling: City
 Polling: Neighborhood
 Populations and Samples

MA.912.S.2.3: Identify sources of bias, including sampling and non-sampling errors.

 Polling: Neighborhood
 Populations and Samples

MA.912.S.3: Learn to work with summary measures of sets of data, including measures of the center, spread, and strength of relationship between variables. Learn to distinguish between different types of data and to select the appropriate visual form to present different types of data.

MA.912.S.3.1: Read and interpret data presented in various formats. Determine whether data is presented in appropriate format, and identify possible corrections. Formats to include:

MA.912.S.3.1.a: bar graphs

 Reaction Time 1 (Graphs and Statistics)

MA.912.S.3.1.c: stem and leaf plots

 Stem-and-Leaf Plots

MA.912.S.3.1.e: histograms

 Histograms
 Real-Time Histogram
 Sight vs. Sound Reactions

MA.912.S.3.1.f: box and whiskers plots

 Box-and-Whisker Plots

MA.912.S.3.1.g: scatter plots

 Correlation
 Least-Squares Best Fit Lines
 Solving Using Trend Lines
 Trends in Scatter Plots

MA.912.S.3.1.h: cumulative frequency (ogive) graphs

 Polling: City
 Populations and Samples

MA.912.S.3.2: Collect, organize, and analyze data sets, determine the best format for the data and present visual summaries from the following:

MA.912.S.3.2.a: bar graphs

 Reaction Time 1 (Graphs and Statistics)

MA.912.S.3.2.c: stem and leaf plots

 Describing Data Using Statistics
 Stem-and-Leaf Plots

MA.912.S.3.2.e: histograms

 Histograms
 Real-Time Histogram
 Sight vs. Sound Reactions
 Stem-and-Leaf Plots

MA.912.S.3.2.f: box and whisker plots

 Box-and-Whisker Plots
 Describing Data Using Statistics

MA.912.S.3.2.g: scatter plots

 Correlation
 Least-Squares Best Fit Lines
 Solving Using Trend Lines
 Trends in Scatter Plots

MA.912.S.3.2.h: cumulative frequency (ogive) graphs

 Describing Data Using Statistics
 Polling: City
 Populations and Samples

MA.912.S.3.3: Calculate and interpret measures of the center of a set of data, including mean, median, and weighted mean, and use these measures to make comparisons among sets of data.

 Box-and-Whisker Plots
 Describing Data Using Statistics
 Mean, Median, and Mode
 Populations and Samples
 Reaction Time 1 (Graphs and Statistics)
 Sight vs. Sound Reactions
 Stem-and-Leaf Plots

MA.912.S.3.4: Calculate and interpret measures of variance and standard deviation. Use these measures to make comparisons among sets of data.

 Polling: City
 Real-Time Histogram
 Sight vs. Sound Reactions

MA.912.S.3.5: Calculate and interpret the range and quartiles of a set of data.

 Box-and-Whisker Plots
 Describing Data Using Statistics
 Mean, Median, and Mode
 Reaction Time 1 (Graphs and Statistics)
 Stem-and-Leaf Plots

MA.912.S.3.6: Use empirical rules (e.g. 68-95-99.7 rule) to estimate spread of distributions and to make comparisons among sets of data.

 Polling: City

MA.912.S.3.7: Calculate the correlation coefficient of a set of paired data, and interpret the coefficient as a measure of the strength and direction of the relationship between the variables.

 Correlation

MA.912.S.3.8: Determine whether a data distribution is symmetric or skewed based on an appropriate graphical presentation of the data.

 Mean, Median, and Mode

MA.912.S.3.9: Identify outliers in a set of data based on an appropriate graphical presentation of the data, and describe the effect of outliers on the mean, median, and range of the data.

 Mean, Median, and Mode

MA.912.S.4: Learn to use simulations of standard sampling distributions to determine confidence levels and margins of error. Develop measures of association between two numerical or categorical variables. Use technological tools to find equations of regression lines and correlation coefficients.

MA.912.S.4.1: Explain and interpret the concepts of confidence level and ?margin of error?.

 Polling: City

MA.912.S.4.2: Use a simulation to approximate sampling distributions for the mean, using repeated sampling simulations from a given population.

 Polling: City
 Populations and Samples

MA.912.S.4.3: Apply the Central Limit Theorem to solve problems.

 Populations and Samples

MA.912.S.4.4: Approximate confidence intervals for means using simulations of the distribution of the sample mean.

 Polling: City

MA.912.S.4.5: Find the equation of the least squares regression line for a set of data.

 Correlation
 Least-Squares Best Fit Lines
 Solving Using Trend Lines

MA.912.S.5: Gather data and determine confidence intervals to make inferences about means, and use hypothesis tests to make decisions. Learn to use data to approximate p-values and to determine whether correlations between variables are significant.

MA.912.S.5.1: Analyze the relationship between confidence level, margin of error and sample size.

 Polling: City

MA.912.S.5.3: Explain and identify the following: null hypothesis, alternative hypotheses, Type I error, and Type II error.

 Polling: City
 Polling: Neighborhood

MA.912.S.5.8: Use a regression line equation to make predictions.

 Correlation
 Least-Squares Best Fit Lines
 Solving Using Trend Lines
 Trends in Scatter Plots

MA.912.S.5.9: Interpret the coefficient of determination, r², for a least-squares regression.

 Correlation
 Least-Squares Best Fit Lines
 Solving Using Trend Lines

Correlation last revised: 5/10/2018

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