Question

1 732.00 10.00

1 795.00 16.00

1 547.00 23.00

1 465.00 21.00

1 1252.00 50.00

1 1255.00 150.00

1 741.00 28.00

1 1151.00 7.70

1 1186.00 2.00

1 754.00 19.00

1 679.00 16.00

1 985.00 5.40

1 1133.00 2.60

1 1139.00 3.10

1 1186.00 3.50

1 984.00 9.10

1 965.00 7.80

1 1084.00 4.10

1 986.00 8.40

1 1023.00 15.00

1 1266.00 25.00

1 1086.00 5.60

1 1044.00 4.60

1 1770.00 8.20

1 1048.00 6.10

1 1641.00 13.00

1 1331.00 6.00

1 1728.00 6.60

1 917.00 5.50

1 1398.00 11.00

1 1763.00 4.50

1 1459.00 4.20

1 2302.00 3.00

1 1614.00 2.30

1 1444.00 2.50

1 2006.00 6.80

1 936.00 19.00

1 1058.00 7.20

1 800.00 6.00

1 1087.00 10.00

1 1329.00 12.00

1 897.00 2.80

1 778.00 .48

1 532.00 .18

1 441.00 .34

1 544.00 .11

1 393.00 .22

1 733.00 .80

1 961.00 8.70

1 886.00 22.00

1 678.00 13.00

1 1011.00 3.50

1 947.00 9.30

1 989.00 21.00

1 1291.00 3.40

1 1186.00 13.00

1 1293.00 5.60

1 1709.00 12.00

1 1425.00 21.00

1 1176.00 8.00

1 980.00 12.00

1 1176.00 6.00

1 989.00 4.70

1 1084.00 31.00

1 1115.00 5.20

1 724.00 27.00

1 847.00 18.00

1 876.00 7.50

1 844.00 3.00

1 908.00 13.00

1 1358.00 7.30

1 1019.00 15.00

4 1300.00 1.30

4 1365.00 4.80

4 1437.00 5.10

4 1460.00 5.10

4 1671.00 4.00

4 1717.00 10.00

4 613.00 12.00

4 353.00 22.00

4 909.00 10.00

4 886.00 11.00

4 890.00 17.00

4 1031.00 9.70

4 1083.00 12.00

4 864.00 4.70

4 886.00 6.00

4 965.00 3.80

4 537.00 17.00

4 630.00 12.00

4 1486.00 1.40

4 1743.00 6.10

4 2061.00 2.80

4 1707.00 4.80

4 862.00 5.70

4 911.00 3.30

4 476.00 3.30

4 743.00 3.70

4 1128.00 9.90

4 848.00 6.80

4 1091.00 13.00

4 715.00 8.80

4 983.00 57.00

4 1251.00 96.00

4 1255.00 360.00

4 1152.00 130.00

4 1085.00 13.00

4 1118.00 61.00

4 1285.00 12.00

4 1178.00 33.00

4 1492.00 48.00

4 1524.00 10.00

4 1473.00 44.00

4 520.00 .43

4 863.00 1100.00

4 549.00 9.40

4 810.00 4.10

4 908.00 2.80

4 804.00 .74

4 1173.00 14.00

4 556.00 22.00

4 659.00 9.10

4 1229.00 140.00

4 1050.00 4.20

4 952.00 12.00

4 826.00 2.00

4 599.00 .30

4 1704.00 1.20

4 1207.00 7.10

4 911.00 180.00

4 1498.00 1.50

4 1496.00 2.40

4 1142.00 4.30

4 879.00 3.90

4 525.00 .99

4 806.00 .45

4 694.00 2.50

4 643.00 .25

4 514.00 .58

4 358.00 2.00

4 856.00 2.20

4 793.00 7.40

4 173.00 .35

4 1433.00 1.90

I would like to know based on the data above: does the weight predict DDT levels in fish with control from flint creek (1) and Spring creek (4)?

Please tell me what the null and alternative hypotheses are, which are the 2 explanatory variables, response variable, and what statistical test you will use.

Please tell me what the results are and explain why you would use it as well, thank you very much!

Answer 1

Step 1 - Put the data in excel as shown and arrange the variables as shown
Replace 4 with 0 in the creek column.

Dependent variable(y)=DDT_level
Independent variable (x)= Creek, Weight

To understand the relationship between the DDT level and weight with creek as a control varible, we run a regression analysis

Step 2 - Select the regression option from the data analysis tab

Step 3- Input the values as shown below.

Step 4 - The output is generated as follows.

From the the regression output(highlighted in yellow) we use the coefficients to get regression equation

DDT_level = 37.0234 - 24.6351 Creek - 0.00033 Weight

To check if this is significant relationship we check the pvalue of the Anova table (highlighted in yellow).

Hypothesis:

H0 : All the beta coefficient are equal to zero.
H1 : At least one of the beta coefficient is not equal to zero.

We see that the pvalue = 0.32 which is greater than 0.05, hence we fail to reject the null hypothesis and conclude that the regression equation is not significant.

Checking the Significance of the explantory variables.

Hypothesis :

H0 : Beta coefficient is equal to zero.
H1 : Beta coefficient is not equal to zero.

Here we look at the pvalue for an individual explanatory variable( highlighted in blue) and if the pvalue is less than 0.05, then we reject the null hypothesis and conclude the variable is a significant predictor.

In this case both the variable, Creek and weight have a pvalue greater than 0.05,hence they are not significant predictor of y.