A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were:y=ax+b a=-1.38 b=39.555 r2=0.693889 r=-0.833 Assume the correlation is significant, and use this to predict the number of situps a person who watches 7 hours of TV can do (to one decimal place)

The Quantitative Environmental Learning Project reported widths and lengths (in centimeters) of a sample of 88 Puget Sound butter clams. Output is shown for the regression of length on width.
Pearson correlation of Width and Length = 0.989
The regression equation is
Length = 0.257 + 1.22 Width
Predictor Coef SE Coef T P
Constant 0.25689 0.09293 2.76 0.007
Width 1.22013 0.01940 62.89 XXXXX
S = 0.3253 R-Sq = 97.9% R-Sq(adj) = 97.8%   Suppose we wanted to use the same data set (butter clam widths and lengths) to set up a confidence interval to estimate how much longer than wide butter clams tend to be. What would be the appropriate procedure?
- -regression
 - paired t 
 -two-sample t
 -chi-square
 -several-sample F

what aspects may impact the r value obtained for our correlation?

A researcher estimates a regression to test the effect of educational attainment (X;) on the average earnings of individuals (Y). The sample correlation coefficient (r) between years of educational attainment and the average earnings of individuals from a samp of 115 individuals was calculated to be 0.29. The value of the regression R will be (Round your answer to two decimal places.) The value of R indicates that the regressor (years of educational attainment) is at predicting the regressand (avera earnings of individuals). good not very good Enter your answer in the answer box. W DOLL e here to search

A statistician finds a Pearson correlation of r = 0.29. What does this correlation tell us about the association between X and Y?

Suppose that you run a correlation and find the correlation coefficient is -0.596 and the regression equation is = 37.37 - 2.9x. The mean for the data values was 5.3, and the mean for the y data values was 21.8. AT Test for the slope of the regression line is performed, and the p-value is greater than the level of significance of 0.05. Use the appropriate method to predict the y value when x is 3.2.

Listed below are systolic blood pressure measurements​ (in mm​ Hg) obtained from the same woman. Find the regression​ equation, letting the right arm blood pressure be the predictor​ (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 9090 mm Hg. Use a significance level of 0.05   Right Arm 100 99 91 79 79   Left Arm 176 171 141 145 143 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is ModifyingAbove y with caretyequals=31.931.9plus+1.41.4x. ​(Round to one decimal place as​ needed.) Given that the systolic blood pressure in the right arm is 90mm​ Hg, the best predicted systolic blood pressure in the left arm is ???? mm Hg. ​(Round to one decimal place as​ needed.)

A psychology professor studies the relationship between anxiety(X) and test performance (Y). Ten students take an anxiety questionnaire prior to taking the final exam. Below is the SPSS printout of the regression equation. Correlations   Anxiety FinalExam Anxiety Pearson Correlation 1 -.691* Sig. (2-tailed)   .027 N 10 10 FinalExam Pearson Correlation -.691* 1 Sig. (2-tailed) .027   N 10 10 *. Correlation is significant at the 0.05 level (2-tailed).   ANOVAa   Model Sum of Squares df Mean Square F Sig.   1 Regression 861.959 1 861.959 7.301 .027b   Residual 944.441 8 118.055       Total 1806.400 9         a. Dependent Variable: FinalExam   b. Predictors: (Constant), Anxiety   Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 125.883…

For a data set of brain volumes (cm") and 1Q scores of ten males, the linear correlation coefficient is r= 0.708. Use the table available below to find the critical values of r. Based on a comparison of the linear correlation coefficient r and the critical values, what do you conclude about a linear correlation? E Click the icon to view the table of critical values of r. The critical values are (Type integers or decimals. Do not round. Use a comma - X separate answers as needed.) Table of critical values of r Number of Pairs of Data n Critical Value of r 0.950 0.878 0.811 0.754 0.707 0.666 0.632 0.602 6 8 9 10 11 12 0.576 Print Done

Consider a regression that uses X = # of 60 pound bench press repetitions to predict Y = maximum bench press amount in pounds…..for the ith student among a sample of high school athletes.  The estimated predicted sample regression is as follows Maxi= 68.91 + .6885Repsi            *the ei is left off for simplicity   The table below lists the actual data from which the regression above was estimated.  For example, a student in the study who trained by doing 12 “60 pound reps” accomplished a maximum bench press amount of 76 pounds.   Xi Yi 12 76 15 82 17 79 3 71   Predict the average maximum bench press for a student that does 17 “60 pound reps”      a)  a.  around 68.85 pounds   b)  b.  around 85.00 pounds   c)  c.  around 80.61 pounds   d)  d.  around 68.91 pounds