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Understanding Business Statistics by Timothy Bergquist, Stacey Jones, Ned Freed

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CHAPTER 11

Basic Regression Analysis

LEARNING OBJECTIVES

After completing the chapter, you should be able to

  1. Describe the nature and purpose of regression analysis.
  2. Calculate the slope and the intercept terms for a least squares line.
  3. Compute and interpret measures of fit, including the standard error of estimate, coefficient of determination, and correlation coefficient.
  4. Discuss the inference side of regression and summarize the basic assumptions involved.
  5. Build interval estimates of the slope and intercept terms in a regression equation.
  6. Conduct a proper hypothesis test for the slope term in a regression equation and interpret the result.
  7. Estimate expected and individual values of y in regression.
  8. Read and interpret a computer printout of results from a simple linear regression analysis.
  9. Check errors (or residuals) to identify potential violations of the assumptions in regression.

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EVERYDAY STATISTICS

Correlation vs. Causation

We've all seen them. Those ‘breakthrough’ headlines that start with “Researchers find link between…” or “New study connects ‘X’ to …” In the past year alone, we've been told that drinking coffee leads to a longer life, prevents Alzheimer's disease, lowers the risk of skin cancer, lessens the probability of heart failure, causes heart failure, decreases the chance of stroke, and leads to vision loss. We've been assured that eating pizza reduces the ...

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