Independ/Depend Samples

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Part 1: Independent Samples t-Test:

Imagine a researcher is interested in the relationships among teachers’ self-esteem and productivity. A randomly selected sample of 40 teachers completed a questionnaire including a number of demographic questions as well as measures to assess their self-esteem and productivity. In the Week 4 Worksheet you will find a table. This table provides the demographic data and participants’ responses for the self-esteem measure (100-point scale) and the productivity measure (50-point scale). Use these data to answer the questions below (these data have already been entered in a SPSS file; see the note below the data table).


In this SPSS assignment, use the tools learned in this course thus far to complete the following:

  1. There are three main assumptions needing to be satisfied before using the independent-samples t-test for testing differences between the genders. Use SPSS to generate the output needed to test the assumptions. Please discuss each one and explain whether each has been met using SPSS output as needed to include the Shapiro-Wilk test for normality (used when the sample size is less than 50), histograms, and the Levene’s test. Keep in mind if the population value is unknown, it is permissible to infer from sample values. Regardless of sample size, test whether these assumptions are met.
  2. Please produce an SPSS output for an independent-samples t-test comparing male and female scores on self-esteem.
  1. What are the null and alternative hypotheses?
  2. Report the results in APA format.
  3. What might be concluded from this hypothetical study (males vs. female self-esteem test)? In the conclusions, please consider possible limitations of the study as well as recommendations for future research.

Part 2: Dependent Samples t-Test:

For Part 2, you will now increase your understanding of inferential statistics involving a dependent samples repeated-measures t-test. Imagine a researcher is interested in whether teachers’ self-esteem differs at the beginning and at the end of the school year. Use the data file “teachersurvey.sav” to conduct a dependent-samples repeated-measures t-test (referred to as a paired-samples t-test in SPSS). In this data set, self-esteem was measured at the beginning of the school year (Score One) and at the end of the school year (Score Two) (i.e., repeated-measures with the same group). These are the variables to be used in this analysis.

Complete the following:

  1. Using self-esteem as the measured variable:
  1. Determine if the two main assumptions underlying repeated-measures t-tests are met. Support your response with SPSS output as needed.
  2. Provide the null and alternative hypotheses.
  3. What are the mean and standard deviation for beginning self-esteem (ScoreOne) and end self-esteem (ScoreTwo) using APA style?
  4. What is the value of Cohen’s d? Is it small, medium, or large?
  5. Interpret the mean, standard deviation, standard error, and confidence interval in the paired-samples t-test output box.
  6. What is the percentage of variance explained? Interpret this value. Report the results in APA format.
  7. What might be concluded from these results? In these conclusions, discuss possible limitations of the study and provide recommendations for future research.
  1. Based on your personal experiences and interests, briefly discuss a potential variable to be compared using a dependent samples repeated-measures t-test.

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Explanation & Answer

Attached.

Running head: INDEPENDENT/DEPENDENT SAMPLES

Independent/dependent samples
Name
Institution

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INDEPENDENT/DEPENDENT SAMPLES

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The main assumptions for the independent t-test are the independent observations,
assumption of normality, and the homogeneity of variance. The assumption for independent
assumptions occurs when there are no associations between the individual cases such that each
observation represents a unique statistical unit (Sedgwick, 2010). Notably, the data comprises a
sample of 40 teachers selected randomly; as such there are no associations between the data
points in each group.
The assumption for normality has it that the dependent variable(s) must assume a normal
distribution for every group of the predictor variables. In the SPSS normality can be tested by the
Shapiro-Wilk test of normality (Sedgwick, 2010).

Tests of Normality
1=male,
Kolmogorov-Smirnova
Shapiro-Wilk
2=female
Statistic
df
Sig.
Statistic
df
Sig.
*
Male
.150
18
.200
.974
18
.863
ScoreOne
Female
.157
22
.172
.932
22
.134
*
ScoreTw Male
.147
18
.200
.937
18
.257
*
o
Female
.118
22
.200
.959
22
.472
*
Male
.148
18
.200
.961
18
.620
ProdOne
Female
.184
22
.051
.875
22
.010
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction

INDEPENDENT/DEPENDENT SAMPLES

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INDEPENDENT/DEPENDENT SAMPLES

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INDEPENDENT/DEPEND...


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