Progress Check

## Use this activity to assess whether you and your peers can:

For a linear relationship, use the least-squares regression line to model the pattern in the data and to make predictions.

Use standard error, and ?2 to assess the fit of a linear equation.

- Directions
- Use the drop-down menu to learn about the three steps needed to complete this assignment.

Three steps to complete the assignment

Context

The *Inclusive Internet Index* assesses and compares countries according to their readiness for the adoption and beneficial use of the internet. Its purpose is to outline the current state of internet inclusion around the world and to help policymakers and influencers gain a clearer understanding of the factors that contribute to wider and sustainable inclusion. The *Inclusive Internet Index* is a study commissioned by Facebook and implemented by the Economist Intelligent Unit

We’ll use the raw data from 2019 or 2020 to determine which of two explanatory variables is the better predictor of the response variable.

Variables

First explanatory variable: *lit-level *= the percentage of a country’s population that can read and write

Second explanatory variable: * percent-schools-w-net = *the percentage of a country’s schools with student internet access

Response variable: *percent-female-net* = the percentage of a country’s female population with internet access

Data

Open the *inclusive-internet* data set in the *Stats at Cuyamaca College* group on StatCrunch ().

Prompt

We’ll use StatCrunch to produce the scatterplot with its least-squares regression line, the regression equation, r-squared, and the standard error for two different regression models. Then we’ll determine which model is the best predictor of the response variable, *percent-female-net*.

Question 1

Using *lit-level* as the explanatory variable and *percent-female-net* as the response variable: graph the scatterplot with its regression line and produce the regression equation with r-squared and the standard error – all at the same time ().

## You should see page 1 of 2 of the StatCrunch output window. Copy all information above the *Parameter estimates:* table (do not copy the tables). Paste the information into your response.

Toggle to page 2 of 2 of the StatCrunch output window. Download the scatterplot with the regression line and embed the .png file with your response.

Write the equation of the regression equation below as displayed in page 1 of 2 of the StatCrunch output window (or even better just copy and paste the equation). Round the values to two decimal places. Identify the slope and y-intercept and interpret each in context.

Identify r-squared (round to 4 decimal places). Then explain what r-squared means in context.

Identify the standard error, Se (round to 2 decimal places). Interpret the standard error in context.

Question 2

Using *percent-schools-w-net* as the explanatory variable and *percent-female-net* as the response variable: graph the scatterplot with the regression line and produce the regression equation with r-squared and the standard error – all at the same time ().

## You should see page 1 of 2 of the StatCrunch output window. Copy all information above the *Parameter estimates:* table (do not copy the tables). Paste the information into your response.

Toggle to page 2 of 2 of the StatCrunch output window. Download the scatterplot with its regression line and embed the .png file with your response.

Write the equation of the regression equation below as displayed in page 1 of 2 of the StatCrunch output window (or even better just copy and paste the equation). Round the values to two decimal places. Identify the slope and y-intercept and interpret each in context.

Identify r-squared and round to 4 decimal places. Then explain what r-squared means in context.

Identify the standard error, Se (round to 2 decimal places). Interpret the standard error in context.

Question 3

## Which regression equation is the best predictor? Use your work in Questions 1 & 2 to explain why the equation is the best predictor.

Question 4

Using the regression equation that is the best predictor, estimate the *percentage of a country’s female population with internet access* if the explanatory variable value is 39.4%. Show some work and state your result in context.

List of StatCrunch Directions

Click here for* StatCrunch Directions*

Module 27 Discussion Board

Use the *Module 27* (opens in a new tab) to ask questions or provide feedback about the problems in any Module 24 activity – including this peer-reviewed assignment.

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