Please help me!!! I missed class the other day and do not udnerstand this for th

Question

Please help me!!! I missed class the other day and do not udnerstand this for the life of me..

Please use Excel Megastat to solve the problem.

Smoking and short-term illness case: (Data at the bottom of the Q's)

Besides the known long-term effects of smoking, some researchers believe that there may be a relationship between the average number of cigarettes smoked and the number of work days missed due to short illnesses. To help understand this, a sample of smokers was drawn. Each person was asked to report the average number of cigarettes smoked per day and the number of days absent from work due to colds last year (sick days).

Use the data file from Blackboard à Lab assignment #4 folder à Lab assignment #4 data. Run the analysis in excel Megastat and answer the following questions. Note that most answers do not need manual calculations and may be reported directly from the Megastat output (there is plenty of space after each question, answers should not be longer than the allocated space).

As understanding of the values and building the skill of reporting data/information, you are asked to interpret the meaning of numerous values.

Answer the following questions:

1. Report the least squares regression equation for predicting the number of sick days as a function of the number of cigarettes smoked?

2. Interpret the practical meaning of the slope of the least squares regression line (1) and the practical meaning of the y-intercept (0). Does the interpretation of 0 make practical sense in the context of this problem/data – why yes/no?

0 (y-intercept) interpretation:

                  1 (slope) interpretation:

3. What percent of the variability in the number of sick days can be explained by knowing the number of cigarettes smoked?

4. Calculate the coefficient of correlation between the independent and dependent variables. Comment on what the magnitude and direction of this correlation coefficient says about the linear relationship between the independent and dependent variables.

5. Using a significance level of = .05, is there sufficient evidence to conclude that the number of cigarettes smoked is useful in predicting the number of sick days from work?

6. Estimate with 95% confidence the average number of sick days for all individuals who smoke 30 cigarettes per day. Interpret the practical meaning of this interval estimate in the context of the problem.

7. Predict with 95% confidence the number of sick days of a single individual who smokes 30 cigarettes per day. Interpret the practical meaning of this interval estimate in the context of the problem.

8. Estimate the true population slope for this least squares regression line with 95% confidence. Interpret the practical meaning of this interval estimate in the context of the problem.

9. What are the variance and standard deviation of the random errors for this regression analysis?

10. Calculate and report the residual of the 10th observation in the data set.

Data-

Cigarettes Days 44 18 41 18 17 18 35 15 33 14 44 15 39 18 35 10 43 16 43 14 41 16 47 19 41 13 30 12 15 18 39 18 36 11 41 13 37 10 43 21 32 13 17 13 34 15 32 11 19 10 44 26 30 13 42 25 34 5 36 8 42 15 47 15 55 19 27 15 28 15 45 22 29 10 37 13 52 13 34 16 48 23 40 15 29 16 34 10 35 19 57 23 48 11 41 10 40 13 36 13 26 7 29 15 52 16 28 16 35 11 42 15 54 19 56 19 37 9 41 17 32 16 63 20 31 15 36 15 31 12 25 15 40 25 55 16 37 21 28 15 56 21 24 16 61 19 40 16 50 14 52 10 45 14 42 19 47 23 22 0 26 12 38 13 46 13 27 9 45 21 43 15 17 11 45 16 40 15 41 17 37 15 30 10 37 14 31 9 49 10 44 15 16 2 25 4 30 5 20 6 36 11 39 14 49 13 37 19 20 11 48 12 28 5 51 16 36 21 42 6 47 9 17 11 22 16 42 21 32 11 31 7 49 16 30 11 31 11 38 18 44 14 41 17 40 20 32 17 48 15 29 17 40 18 45 18 40 15 35 18 37 17 41 16 25 16 35 19 44 15 58 24 27 13 42 22 26 9 48 15 30 11 36 13 26 8 27 6 39 14 17 17 44 21 41 19 26 14 30 14 36 13 31 15 55 17 45 17 27 17 25 9 42 15 18 6 49 15 60 19 40 18 29 15 32 12 35 16 45 15 42 11 52 13 52 16 8 16 36 15 33 12 38 17 38 11 38 14 36 16 44 11 36 14 35 12 30 13 39 21 37 7 26 22 51 18 42 10 44 19 41 15 32 16 56 19 47 22 39 11 18 10 33 12 49 14 16 7 38 9 27 8 26 15 27 8 25 15 14 11 40 9 38 9 38 13 62 18 47 14 54 9 37 6 40 17 56 17 38 16 53 22 52 19 21 11 34 16 23 5 44 13 36 17 45 14 23 10 26 12 54 20 37 19 56 11 38 14 59 18 39 16 38 21 42 20 44 17 32 17 45 13

Explanation / Answer

Result from Excel :-

1) y- number of sick days

x- number of cigarattes

y^ = 7.28653 + 0.18974253*x

2) slope of the least squares regression line (1) is 0.18974253

it can be interpreted as if we take 1 more cigaratte ,then the number of sick days will increase by 0.18974253

the practical meaning of the y-intercept (0).

-if anyone don't smoke cigaratte , they will be sick in 7.28653 days

3) percent of the variability in the number of sick days can be explained by knowing the number of cigarettes smoked is given by R^2 =   0.19686635

4)   the coefficient of correlation between the independent and dependent variables. = r = sqrt(R^2) = sqrt(0.19686635) = 0.4436962

5) since p-value of b1 is 1.46E-12

which is very very small

,less than 0.05

hence there is sufficient evidence to conclude that the number of cigarettes smoked is useful in predicting the number of sick days from work

Please ask rest question again, As per chegg guideline we are supposed to answer first 4 subparts , which i solved .

SUMMARY OUTPUT Regression Statistics Multiple R 0.443696244 R Square 0.196866357 Adjusted R Square 0.193359224 Standard Error 3.996685058 Observations 231 ANOVA df SS MS F Significance F Regression 1 896.6419 896.6419 56.13312 1.46E-12 Residual 229 3657.93 15.97349 Total 230 4554.571 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 7.286531113 0.988868 7.368559 3.11E-12 5.338088 9.234974 5.338088 9.234974 X Variable 1 0.189742532 0.025325 7.492204 1.46E-12 0.139842 0.239643 0.139842 0.239643

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