a. To determine Carry out a rank order transformation of the data in problem 4. Carry out appropriate test using transformed data. Explain the test to someone who does not know about rank-transformation or rank-order test but that person knows about parametric test procedure. Explanation Calculation: In this problem t -test is useful for comparing means. In problem 4, it has solved. At first the scores should be arranged in ascending order and those will be ranked. Ascending order Rank 1.2 1 2.1 2 2.5 3 3.8 4 4.3 5 4.8 6 5.7 7 6.7 8 7.2 9 9.2 10 After the rank order transformation, the rank-order scores are given in the below table: Group A Rank order score Group B Rank order score 1.2 1 2.1 2 2.5 3 9.2 10 4.3 5 5.7 7 3.8 4 6.7 8 7.2 9 4.8 6 There are two populations: Population 1: Group A. Population 2: Group B. The null hypothesis is that the means of the two populations are same. That is, if μ i , i = 1 , 2 is the i th population mean , then the null hypothesis is ( μ 1 = μ 2 ) . The research hypothesis is that the two populations do not have the same mean. Step-by-step procedure to obtain the t-value and p-value using the SPSS software: Enter the data in a column in data view . It is assumed that group A is dented as ‘1’ and group B is denoted by ‘2’. Enter the scores in another column as ‘data’ corresponding to the data in data view . Go to Analyze > Compare means >Independent-Samples T Test . Send the data in test variable and group in grouping variable . Click on define groups . Under Group 1 write ‘ 1 ’ and Group 2 write ‘ 2 ’> click continue. Click Ok. The SPSS output is given below: From the output the t -value is –1 b. To determine Carry out a rank order transformation of the data in problem 5. Carry out appropriate test using transformed data. Explain the test to someone who does not know about rank-transformation or rank-order test but that person knows about parametric test procedure. c. To determine Carry out a rank order transformation of the data in problem 6. Carry out appropriate test using transformed data. Explain the test to someone who does not know about rank-transformation or rank-order test but that person knows about parametric test procedure.

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ISBN: 9780205258154

Author: Arthur Aron Ph.D., Elaine N. Aron Ph.D., Elliot Coups Ph.D., Cole Publishing

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Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Chapter 14, Problem 11PP

To determine

Carry out a rank order transformation of the data in problem 4.

Carry out appropriate test using transformed data.

Explain the test to someone who does not know about rank-transformation or rank-order test but that person knows about parametric test procedure.

To determine

Carry out a rank order transformation of the data in problem 5.

Carry out appropriate test using transformed data.

Explain the test to someone who does not know about rank-transformation or rank-order test but that person knows about parametric test procedure.

To determine

Carry out a rank order transformation of the data in problem 6.

Carry out appropriate test using transformed data.

Explain the test to someone who does not know about rank-transformation or rank-order test but that person knows about parametric test procedure.

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Chapter 14, Problem 10PP

Chapter 14, Problem 12PP

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