Completely Randomized Factorial Anova

Exercises 10.59 and 10.61 require the use of the “One-Way ANOVA” function within the Data Analysis menu in Excel. Refer to Appendix E10 for instructions on using Excel for these exercises.

1.What two factors did you investigate in your procedure, and why did you choose to compare these two factors?

State the independent variable (IV) and the dependent variable (DV) from the case study Level C, Case 2.

2. Compute the means for the following set of scores saved as Ch. 2 Data Set 3 using IBM® SPSS® software. Print out a copy of the output. (Please refer to attachment)

When you perform a test of hypothesis, you must always use the 4-step approach: i. S1:the “Null” and “Alternate” hypotheses, ii. S2: calculate value of the test statistic, iii. S3: the level of significance and the critical value of the statistic, iv. S4: your decision rule and the conclusion reached in not rejecting or rejecting the null hypothesis. When asked to calculate p–value, S5, relate the p-value to the level of significance in reaching your conclusion.

Single-subject design (p. 238) – using just one participate or very few participants to study the influence of a new procedure (2012, p. 238).

If 9 t tests were conducted and the set alpha for this study is 0.05, then the alpha level that should be used to determine the differences between the two groups is 0.05/9=0.0056 and the resulting alpha will be used to determine significant differences.

They used with an experimental control group and they compared it for over a period of 5 years. The observation they studied was to compare the effects on the experiment and compared the group of students using: “(a) descriptive statistics including means and standard deviations of direct observation data; (b) visual inspection of means for DIBELS subtests across first, second, and third grades; (c) ANOVA test for the slopes for NWF (first grade) and ORF (first-third grades); and (d) ANOVA tests for the WRMT.” (Wills, H.,

where n is the sample size, t is the t-student value for the respective level of

The t-test is a parametric analysis technique used to determine significant differences between the scores obtained from two groups. The t-test uses the standard deviation to estimate the standard error of the sampling distribution and examines the differences between the means of the two groups. Since the t-test is considered fairly easy to calculate, researchers often use it in determining differences between two groups. When interpreting the results of t-tests, the larger the calculated t ratio, in absolute value, the greater the difference between the two groups. The significance of a t ratio can be determined by comparison with the critical values in a

At the bottom of SPSS, there are options to look at the data in Data View or in Variable View. I clicked on Variable View to name my variables. A list of columns appeared, but I only made changes to rows in the Name column. In row 1 under Name, I typed SubjectNo (no spaces or symbols are allowed when naming variables in SPSS) for Subject Number. I clicked back to Data View. The first column was now named SubjectNo, so I typed the list of subject numbers from 1 to 96 (1 number per row) for the number of "participants" in this study. I go back to Variable View and named row 2 as GroupNo. Under the GroupNo column, within Data View, I typed 1’s in rows 1 thru 48 and typed 2’s in rows 49-96. Group 1 was high need for cognition and group 2 was low need for cognition. I labeled the next 45 rows under GroupNO, in the Variable View, as the different item numbers: Item#1 thru Item#45. In all there was a total of 47 rows in the Variable View and 47 columns in the Data View. I clicked back into random.org and highlighted all 4,320 integers not missing any and right clicked for a menu to pop up. In this menu I clicked COPY, then I went back to the SPSS datasheet in the Data View. Under the column labeled Item#1, I clicked on the cell in row 1 and right clicked for the Paste option. All 4,320 integers were placed correctly in the columns, Item#1-Item#45 in 96

The second research question addressing peer relationships, the variables that will be used in the analysis include friendships and the rate of smoking. Lastly, the third research question, the variables that will be used in the analysis include sex and rate of beginning smoking. The first research question will be analyzed using a one-way ANOVA, the second research question will be analyzed using a chi-square test and the last research question will be analyzed using a chi-square test as well. The data being categorical is what determines the test above. By converting the SAS data to excel, the test will run on Graph Pad Prism 7 to show the association between smoking and Latino youth. It will also, reveal if the participants are more at risk or a higher risk for smoking depending upon the second

After running the factor analysis on 124 responses, four different factors came out of 12 variables. The four factors are given as below:

Using the data from SPSS output, the P-value (represented by “Sig.” – One Way DataSet 1\residential sales.sav) found on the second table – ANOVA is 0.140.

In terms of independent variables, by referring to the Appendix, figure 1 reveals the summary of the sample; it also