Step 1a: M_D and _D

First, calculate the difference score for each individual by subtracting the score in condition 1 from the score in condition 2. Put the difference scores in cells C2 to C26. Calculate the mean difference score and put the result in cell H2.

Usually, no difference is predicted between two conditions based on the null hypothesis H₀. Thus, _D = 0. This is displayed in cell G4.

Step 1b: s_MD

In the next step, we need to calculate the standard error of the mean. For this, we use the following formula:

sMD=sn

Let's break this down into its components. First, we need to calculate the variance s² so we can calculate the standard deviation s. Here is the formula for calculating the variance s₂:

s2=SSn1=SSdf

Calculate the sum of squares. You will do this the same way you calculated SS for t-scores (i.e., LL8 and LL9). First, subtract each difference scores from the mean difference score in column D. Then, square these values to get the squared deviations from the mean difference in column E. Sum these values and put the answer in cell H5. Put the degrees of freedom df in cell H6. Now we can calculate the variance. Do so in cell H7. Next, take the square root of the variance s² to get the standard deviation s. Put the result in cell H8.

s=s2

Finally, to get s_MD, take the standard deviation s, and divide it by the square root of the number of difference scores n. Put the result in cell H9.

sMD=sn

Step 1c: T-value

Calculate the value for t based on the quantities you calculated in the previous steps. Again, use the following formula for t:

t=MDDsMD

Save your work

Step 2: Determine the one-tailed and two-tailed probabilities As we saw in the previous lesson, Excel has a build-in function to calculate probabilities with a t-test. This function is called =TTEST(). This function takes four input arguments; the data for the first condition (array 1), the data for the second condition (array 2), whether the test is one-tailed or two-tailed (nondirectional), and the type of test.

One-tailed probability test

We will calculate the one-tailed probability for the paired sample t-test in cell H16. For array 1, you want to select the data for condition 1 (cells A2:A26. For array 2, you want to select the data for condition 2 (cells B2:B26). First, we will do a one-tailed (directional) test of the null hypothesis H0. To do so, put in the value 1 for Tails. For Type, put in the value 1. This corresponds to a paired sample t-test. Thus, the formula in cell H16 should say = TTEST(A2:A26,B2:B26,1,1). A probability should appear in cell H16 after you hit Enter.

Two-tailed probability test

Now, perform a two-tailed probability test on the data by adjusting the formula for the t-test and putting the answer in cell H17. Save your work

Step 3: Making inferences

Based on the probabilities you found for the one-tailed and two-tailed t-test, answer questions Q1 and Q2 in cells I16 and I17. Put your Yes/No answer in cells J16 and J17.

Save your work

Step 4: Comparing the independent sample and paired sample t-test Finally, go back to the previous learning lab and review the results. Compare them to the results you got in this learning lab. You should find that even though the data were the same in the two cases, the result of the t-test is different.

Answer question Q3 displayed in cells I19 and I20 by putting your Yes/No answer in cell J20

Save your work Submitting:To complete the learning lab, you need to submit your Excel file with answers. The name of your Excel file should have the following structure:PSYCH200_LL10_your lab

LL9 - Compatibility Mode - Excel Search (Alt+Q) Anna Prater AP X X AutoSave Off Comments Share File Home Insert Page Layout Formulas Data Review View Help 11 ~ A A" EE ab General Conditional Formatting Insert Calibri AYO $ ~ % " Format as Table Delete Sort & Find & Analyze Sensitivity Paste = $58 308 Cell Styles * Format Filter * Select ~ Data Font Alignment Number Styles Cells Editing Analysis Sensitivity Undo Clipboard 15 A B C D E F G H I J K M N Group 1 (X1-M1) Group 2 (X2-M2)2 90 290.3616 85 344.4736 Mean G1 72.96 75 4.1616 65 2.0736 Mean G2 66.44 UI AWNP 63 99.2016 53 180.6336 Ho difference 85 144.9616 64 5.9536 SS1 77 16.3216 65 2.0736 SS2 45 781.7616 64 5.9536 df1 LD 00 75 4.1616 59 55.3536 df2 73 0.0016 63 11.8336 $ 2 10 85 144.9616 75 73.2736 s(M1-M2) 11 64 80.2816 62 19.7136 12 51 482.2416 68 2.4336 13 63.3616 35 988.4736 T value 14 85 144.9616 90 555.0736 15 68 24.6016 76 91.3936 T-test probability 75 85 344.4736 Y/N 16 4.1616 One-tailed: Q1: Based on a one-tailed test with a = .05, the researcher would reject Ho 17 56 287.64 58 2.4336 Two-tailed: Q2: Based on a two-tailed test with a = .05, the researcher would reject Ho Y/N 18 95 485.7616 62 19.7136 19 76 9.2416 71 20.7936 20 83 100.8016 70 12.6736 21 76 9.2416 70 12.6736 Sheet1 Sheet2 Sheet3 + + 100% Ready 2:01 AM Type here to search O W X 53OF D D ) ENG 12/6/2021