Activity 3: Making Inferences with Scatterplots
Activity
Students will be able to organize data into a scatterplot and look for trends and characteristics using Excel.
Students will be able to generate the line of regression using Excel and interpret its meaning in context.
Students will be able to make predictions and infer with the line of regression without extrapolation.
Prerequisite Knowledge
Rationale
Using the scenario initially presented at the start of the unit, students will determine if the female or male students performed better on a specific assessment with the use of inferential statistics and technology. The students will create a scatterplot of the boy, girl, and boy and girl data combined to identity any trends or relationships. The students will then calculate the line of regression for each scatterplot and attempt to make a prediction about the entire female population and male population tested from the provided sample.
CCGPS Standards Addressed
Students will be able to organize data into a scatterplot and look for trends and characteristics using Excel.
Students will be able to generate the line of regression using Excel and interpret its meaning in context.
Students will be able to make predictions and infer with the line of regression without extrapolation.
Prerequisite Knowledge
- Students should be able calculate and interpret the slope and y-intercept of a linear equation
- Students should be able to identify the independent and dependent variables of an association
Rationale
Using the scenario initially presented at the start of the unit, students will determine if the female or male students performed better on a specific assessment with the use of inferential statistics and technology. The students will create a scatterplot of the boy, girl, and boy and girl data combined to identity any trends or relationships. The students will then calculate the line of regression for each scatterplot and attempt to make a prediction about the entire female population and male population tested from the provided sample.
CCGPS Standards Addressed
- MCC8.SP.1 Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association. (8th grade)
- MCC8.SP.2 Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line. (8th grade)
- MCC9‐12.S.ID.6 Represent data on two quantitative variables on a scatter plot, and describe how the variables are related. (9th grade)
- MCC9‐12.S.ID.7 Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data. (9th and 10th grade)
- MCC9‐12.S.ID.8 Compute (using technology) and interpret the correlation coefficient of a linear fit. (9th grade)
- MSRAD3. Students will determine if an association exists between two variables (pattern or trend in bivariate data) and use values of one variable to predict values of another variable. (12th grade)
- Make sense of problems and persevere in solving them.
- Reason abstractly and quantitatively.
- Construct viable arguments and critique the reasoning of others.
- Use appropriate tools strategically.
- Attend to precision.