Ψ 420AinsworthLab 1Data Set 145 45 23 2342 43 10 4033 16 25 4227 31 43 3235 44 42 3728 18 29 1914 38 38 5032 29 25 261. Using data set 1:a. By hand – calculate the mean, sample standard deviation, estimated population SD, estimated population variance and the standard error. What is the difference between the four measures of variability?b. By computer (using SPSS) – i. Input data 1 as a single variable and label it “data1”1. In the main SPSS screen switch to variable view by clicking on the “variable view” tab at the bottom of the screen.2. In the first row under “name” type in data1.3. Switch back to data view and the first column should be labeled data1 now.4. Type in the data above by columns (e.g. column 1, column 2, etc.).ii. Check answers from “a”.1. In SPSS go to Analyze -> Descriptive Statistics -> Descriptives. Highlight data1 and click on the arrow in the center to move data1 over.2. Click on the “options” button and select mean, std. Deviation, variance, S.E. mean, (add skewness and kurtosis); deselect everything else. 3. Click on continue -> OK.iii. Using “Explore”, create a histogram along with a test of the data for normality and the presence of outliers.1. Go to analyze -> descriptive statistics -> explore.2. Move data1 over.3. Click on statistics and make sure that both descriptives and outliers and click continue.4. Click on plots, select “none” under boxplots, deselect stem-and-leaf and select histogram and click on continue. And then click on OK.2. Change the bold number in “data set 1” to 78 and re-run “1.b.iii”, follow the samedirections.Ψ 420AinsworthData Set 2ResponseYes NoTreatment Group 34 19 53Control Group 26 27 5360 46 1063. Using data set 2:a. By hand – calculate the chi-square for the relationship between the two discrete variables. Is there a relationship? Refer to table A.2 in the appendix.b. By computer – check your answer to “a”.i. Using the same SPSS data window, create a new variable and labelit “Group” -> click on values and 1 = treatment and 2 = control. Create a new variable and label it “Response” -> click on values and 1 = yes and 2 = no. ii. In the group variable enter 53 “1’s” down the column and then enter 53 “2’s” down the column.iii. In the Response column enter 34 “1’s” and then 19 “2’s”; enter 26 “1’s” and then 27 “2’s”.iv. Go to analyze -> descriptive statistics -> crosstabs. Put group in rows and response in columns. Click on statistics and select chi-square, click on continue -> OK.4. Using data set 3:a. By hand – compute correlation and regression for the two continuous variables.b. By computer – check the answers from “a” and annotate the output. i. Create two new variables “height” and “number”. Enter the data the way it is seen to the left (without the plant numbers)ii. Analyze -> Correlate -> Bivariate. Highlight both height and number and move them over to the variables box. Click on OK.Data Set 3PlantHeight ofPlantNumber ofSeeds1 20 422 17 383 19 454 21 485 20 446 20 437 22 468 21 459 16 3910 24 5511 22 4912 24 5513 21 4314 19 3815 21 5116 20 4617 15 40Ψ 420Ainsworthiii. Analyze -> Regression -> Linear. Move number over into “dependent” and height over into “independent(s)”. Click on OK.c. Generate a scatterplot and describe it.i. Graphs -> Legacy Dialogs -> “Scatter/dot…”. Click on simple -> Define. Move height into x-axis and number into y-axis. Click on OK.5. Using data set 3:a. By hand – i. Perform an independent samples t-test.ii. Perform a dependent samples t-test (assuming each person is in both the treatment and control, the answers #1 and #11 are from the same person, etc.)b. By computer – i. Redo “a” as an independent samples t-test to check “a” answer. Annotate theoutput.1. Create a group and an anger variable, label the group variable appropriately. 2. Analyze – Compare Means – Independent samples T-Test. Move Anger into test variable and group into grouping variable -> Define groups and put a 1 in group1 and a 2 in group 2. Continue -> OK.ii. Perform a matched pair (dependent samples) t-test. Assume that every subject participates in the treatment and control. Annotate the output.1. Create two new variables; control and treatment.2. Rearrange the data to the in data set 3 so that the first person has a score of 15 on a control and a score of 8 on treatment, and so on down the . 3. Analyze -> Compare Means -> Paired samples T-Test. Highlight both treatment and control -> move them both over to create a pair of variables in the “paired variables” box. Click on OK.iii. How are “i” and “ii” different and why?Data set 3Group Anger Level1 Control 152 Control 123 Control 124 Control 55 Control 116 Control 137 Control 98 Control 79 Control 1010 Control 711 Treatment 812 Treatment 1013 Treatment 614 Treatment 515 Treatment 716 Treatment 517 Treatment 918 Treatment 819 Treatment 320 Treatment