MATH 225N Week 8 Stats Assignment-Performing Linear Regressions with Technology | Performing Linear Regressions with Technology
MATH 225N Week 8 Stats Assignment-Performing Linear Regressions with Technology Week 8 Stats Assignment- Performing Linear Regressions with Technology Determine the best fit linear regression equation using Technology - Excel Question The table below shows data on annual expenditure, x ( in dollars), on recreation and annual income, y (in dollars), of 20 families. Use Excel to find the best fit linear regression equation. Round the slope and intercept to the nearest integer Question An economist is studying the link between the total value of a country's exports and that country's gross domestic product, or GDP. The economist recorded the GDP and Export value (in millions of $'s) for 30nations for the same fiscal year. This sample data is provided below. Correct answers: Calculate the correlation coefficient using Technology - Excel Question An economist is trying to understand whether there is a strong link between CEO pay ratio and corporate revenue. The economist gathered data including the CEO pay ratio and corporate revenue for 30 companies for a particular year. The pay ratio data is reported by the companies and represents the ratio of CEO compensation to the median employee salary. The data are provided below. Use Excel to calculate the correlation coefficient r between the two data sets. Round your answer to two decimal places. - - - - - - - - - - - - - - - -- The correlation coefficient can be calculated easily with Excel using the built-in CORREL function. 1. Open the accompanying data set in Excel. 2. In an open cell, type "=CORREL(A2:A31,B2:B31)", and then hit ENTER. You could label the result of this cell by writing "Correlation coefficient" or "r" in an adjacent open cell. The correlation coefficient, rounded to two decimal places, is r≈0.50.
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math 225n week 8 stats assignment performing linear regressions with technology | performing linear regressions with technology
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performing linear regressions with technology
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the table below shows data