Positive versus negative correlation

    • [DOC File]Regression Analysis: t90 versus t50

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      The correlation coefficient r is a measure of the linear relationship between two variables paired variables x and y.. For data, it is a statistic calculated using the formula. r = The correlation coefficient is such -1 ≤ r ≤ 1. If y is a linear function of x, then r =1 if the slope is positive and -1 if it is negative.

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    • [DOCX File]Avon Community School Corporation / Homepage

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      Over the past few years, there has been a strong positive correlation between the annual consumption of diet . soda drinks and the number of traffic accidents. a) Do you think increasing consumption of diet soda drinks causes traffic accidents? b) What lurking variables might be causing the increase in one or both of the variables? Explain. 8.

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    • [DOC File]Worksheet on Correlation and Regression

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      Worksheet for Correlation and Regression (February 1, 2013). Part 1. Consider the following hypothetical data set. Here are data from four students on their Quiz 1 scores and their Quiz 5 scores and a graph where we connected the points by a line.

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    • [DOC File]14 college.edu

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      Is there a positive correlation, negative correlation or no correlation? (a) Shoe size versus height (b) Shoe size versus salary (c) Hours of exercise per week versus weight. Linear (Pearson) Correlation Coefficient, r: r measures the strength of the linear relationship between paired x- and y- …

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    • [DOCX File]blossoms.mit.edu

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      A positive correlation means the variables increase or decrease at the same time: A negative correlation means that one variable increases as the other decreases: Examples of STRONG versus WEAK correlation. A correlation is called “strong” when the variables move together almost in unison: A correlation is called “weak” when the ...

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    • [DOC File]Correlation Exercises - University of Kentucky

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      Correlation. INSTRUCTIONS: Read each of the descriptions below. Then determine whether the relationship described suggests a positive or negative correlation. Then consider why we might find this relationship. The more you think about the correlation suggested the more possible explanations for this relationship you are likely to find.

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