What is the simple least-squares regression model? What are the requirements to perform inference on a simple least-squares regression line? How do we verify that these requirements are met?
Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 25m
- 9. Hypothesis Testing for One Sample3h 57m
- 10. Hypothesis Testing for Two Samples4h 50m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - Excel12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - Excel9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - Excel21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - Excel12m
- 11. Correlation1h 24m
- 12. Regression1h 50m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA1h 57m
12. Regression
Linear Regression & Least Squares Method
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Join thousands of students who trust us to help them ace their exams!Watch the first videoMultiple Choice
The scatterplot below shows a set of data and its least-squares regression line. Based on the graph, which of the following is most likely the equation of the regression line?

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Verified step by step guidance1
Step 1: Observe the scatterplot and the regression line. The regression line has a negative slope, as it decreases from left to right. This indicates that the coefficient of x in the equation must be negative.
Step 2: Identify the y-intercept of the regression line. The line crosses the y-axis at approximately 50, which suggests the constant term in the equation is close to 50.9.
Step 3: Compare the slope visually. The slope of the line appears to be steep, suggesting a larger absolute value for the slope coefficient. Among the options provided, the slope of -4.1 matches the visual steepness.
Step 4: Eliminate incorrect options. Based on the negative slope and the y-intercept near 50.9, eliminate equations with positive slopes or incorrect intercepts.
Step 5: Select the equation that matches both the slope and y-intercept. The correct equation is ŷ = -4.1x + 50.9.
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