# Escitalopram

By E. Akascha. Southern Methodist University. 2018.

In the “Bivariate Correla- tions” box escitalopram 5mg fast delivery, be sure Flag significant correlations is checked 20 mg escitalopram with visa. Significance Testing of the Spearman Correlation Coefficient Interpret the output for a Spearman rS like the Pearson r escitalopram 20 mg line. For example, say that we test the influence of the independent variable of the color of a product’s label (Blue or Green) on the dependent variable of how desirable it is, obtaining these scores: Independent Variable: Color Condition 1: Condition 2: Blue Green 10 20 12 24 14 28 17 19 16 21 Name the variables: In the Data Editor, name one variable using the independent variable (Color) and one using the dependent variable (Desire. However, it is very helpful to have output in which the con- ditions are labeled with words and not 1s and 2s. Therefore, while in variable view in the Data Editor, in the row for the independent variable, click on the rectangle under “Values” and then in it click the gray square with the three dots. To enter each dependent score, first identify the condition by entering the condition’s number under “color. In the sixth row, enter 2 (for Green) under “color,” with 20 under “desire,” and so on. For example, say that we study the total errors made in estimating distance by the same people when using one or both eyes. We obtain these data: One Eye Two Eyes 10 2 12 4 9 6 8 Enter the data: In the Data Editor, create two variables, each the name of a condi- tion of the independent variable (for example, One and Two). Then in each row of the Data Editor, enter the two dependent scores from the same participant; for example, in row 1, enter 10 under One and 2 under Two. Select the variables: In the area under “Paired Variables,” drag and drop each of your variables into the highlighted row labeled “1. The output also includes the “Paired Samples Statistics” table, containing the X and sX in each condition. In the “Paired Samples Correlations” table is the Pearson r between the scores in the two conditions. We have these data: Condition 1: Condition 2: Condition 3: Blue Green Yellow 10 20 24 12 24 25 14 28 26 17 19 21 16 21 23 Enter the data: Enter the data as we did in the independent-samples t-test: Name one variable for the independent variable (for example, Color) and one for the depend- ent variable (Desire). Again identify a participant’s condition by entering the condi- tion’s number in the Color column (either a 1, 2, or 3). Label the output: Use words to label each level, as we did in the independent- samples t-test. Select Descriptive: Click Options and, in the “Options” box, checkmark Descrip- tive to get the X and sX of each level. In the “Descriptives” table, the first three rows give the X, sX and confidence interval for in each level. Under “(I) color” is first Blue, and in the rows here are the comparisons between Blue and the other conditions. Thus, the first row compares the mean of Blue to the mean of Green and the difference is 28. The confidence interval is for the difference between the s represented by these two level means. Under “(I) color” at Green are the comparisons involving the mean of Green, including again comparing it with Blue. Note in your output the line graph of the means, which may be exported to a report you are writing. Name the variables: In the Data Editor, name three variables: one for factor A (Volume), one for factor B (Gender), and one for the dependent variable (Persuasion). Let’s use 1, 2, and 3 for soft, medium, and loud, and 1 and 2 for male and female, respectively. Label the output: Enter word labels for each factor as described in the independent- samples t-test (B. In the Data Editor, enter a participant’s level of A in the Volume column and, in the same row, enter that participant’s level of B in the Gender column. While still in the same row, enter that participant’s dependent score in the Persuasion column. Thus, in the male-soft cell is the score of 9, so we enter 1 under Volume, 1 under Gender, and 9 under Persuasion. In row 4 of the Data Editor, for the first male-medium score, enter 2 under Volume, 1 under Gender, and 8 under Persuasion, and so on.