6.09 Linear regressions and residual plots
Interactive practice questions
Consider the following set of data.
| $x$x | $15.7$15.7 | $13.1$13.1 | $16.1$16.1 | $11$11 | $18.6$18.6 | $15.8$15.8 | $12.7$12.7 | $12.8$12.8 | $14.3$14.3 | $16.8$16.8 |
|---|---|---|---|---|---|---|---|---|---|---|
| $y$y | $28.3$28.3 | $28.8$28.8 | $28.4$28.4 | $29$29 | $27.9$27.9 | $28.4$28.4 | $28.5$28.5 | $29$29 | $28.5$28.5 | $28.6$28.6 |
Using a graphics calculator (or other technology), calculate the correlation coefficient between these scores.
Give your answer to two decimal places.
Choose the description which best describes the statistical relationship between these two variables.
Strong positive linear relationship
Weak relationship
Moderate negative linear relationship
Moderate positive linear relationship
Strong negative linear relationship
Using a graphics calculator (or other technology), form an equation for the least squares regression line of $y$y on $x$x.
Give your answer in the form $y=ax+b$y=ax+b. Give all values to one decimal place.
Consider the following set of data.
The forecast maximum temperature, in degrees Celsius, and the observed maximum temperature are recorded to determine the accuracy in the temperature prediction models used by the weather bureau.
Research on the number of cigarettes smoked during pregnancy and the birth weights of the newborn babies was conducted.