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Lecture Slides

This chapter introduces methods for determining the existence and linearity of correlations between variables, as well as analyzing differences between predicted and actual values. It also covers correlations among three or more variables and developing mathematical models for nonlinear correlations.

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Lecture Slides

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  1. Lecture Slides Essentials of Statistics5th Edition and the Triola Statistics Series by Mario F. Triola

  2. Chapter 10Correlation and Regression 10-1 Review and Preview 10-2 Correlation 10-3 Regression 10-4 Variation and Prediction Intervals 10-5 Rank Correlation

  3. Section 10-1 Review and Preview

  4. Review In Chapter 9 we presented methods for making inferences from two samples. In Section 9-4 we considered two dependent samples, with each value of one sample somehow paired with a value from the other sample. In Section 9-4 we considered the differences between the paired values, and we illustrated the use of hypothesis tests for claims about the population of differences. We also illustrated the construction of confidence interval estimates of the mean of all such differences. In this chapter we again consider paired sample data, but the objective is fundamentally different from that of Section 9-4.

  5. Preview In this chapter we introduce methods for determining whether a correlation, or association, between two variables exists and whether the correlation is linear. For linear correlations, we can identify an equation that best fits the data and we can use that equation to predict the value of one variable given the value of the other variable. In this chapter, we also present methods for analyzing differences between predicted values and actual values.

  6. Preview In addition, we consider methods for identifying linear equations for correlations among three or more variables. We conclude the chapter with some basic methods for developing a mathematical model that can be used to describe nonlinear correlations between two variables.

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