Copyright © 2014 Pearson Education, Inc.12-1 SPSS Core Exam Guide for Spring 2014 The goal of this...

Copyright © 2014 Pearson Education, Inc. 12-1

SPSS Core Exam Guide for Spring 2014

The goal of this guide is to:Be a side companion to your study, exercise and exam

completion – it is not a substitute for reading through your book chapters

Chronologically shortlist different analyses by chapter andDisplay must have information needed for the running,

reading and understanding of the generated outputs.


Good to know about the exam:

Goals:This exam is designed to test your ability to work with SPSS,As well as to interpret the results of the analysesIf you write out the steps for your analyses you can get partial

credit even if you do not get the right answerWhat can you use to show your understanding:This guide andThe textbook (if you do not have notes in it)What you cannot use:Smartphones, mail, internet or help from your peers

Chapter 12Using Descriptive Analysis

Performing Population Estimatesand Testing Hypotheses

Copyright © 2014 Pearson Education, Inc. 3


E1: Measures of Variability: Visualizing the Diversity of Respondents


E2: Describing responses to a question


Statistical Inference: Sample Statistics and Population ParametersStatistical inference is a set of procedures in which the sample

size and sample statistic are used to make an estimate of the corresponding population parameter.

Two types of statistical inferences:Parameter estimate is used to approximate the population

value (parameter) through the use of confidence intervals.Hypothesis testing is used to compare the sample statistic

with what is believed (hypothesized) to be the population value prior to undertaking the study.


Statistical Inference: Sample Statistics and Population ParametersA sample statistic is usually a mean or percentage.Standard error is the measure of variability in the sampling

distribution.A confidence interval is the degree of accuracy desired by the

researcher stated in the form of a range with an upper and lower boundary.90% - lie within +/- 1.64 standard deviations95% - lie within +/- 1.96 standard deviations99% - lie within +/- 2.58 standard deviations


E3: Inferring the measure of the true population answer towards a certain question given a CI.


Hypothesis TestsTests of an hypothesized population parameter value:

Test of an hypothesis about a percent or a meanThe crux of statistical hypothesis testing is the sampling

distribution concept.In statistics, the t-statistic is a ratio of the departure of an

estimated parameter from its notional value and its standard error.Does not hold if2-tailed significance < 0.05 and outside +/- 1.96 St.DHolds if2-tailed significance >/= 0.05 and within +/- 1.96 St.D


E4: Testing a hypothesis that the population will give a specific answer or display a parameter

Chapter 13Implementing Basic Differences Tests


Differences Between Percentages with Two Groups (Independent Samples)

Independent samples are treated as representing two potentially different populations.

Null hypothesis: the hypothesis that the difference in the population parameters is equal to zero

With a differences test, the null hypothesis states that there is no difference between the percentages (or means) being compared.

Significance of differences between two percentages - alternative to the null hypothesis is that there is a true difference between the population parameters.


E5:Testing differences b/n the means of two groups (Independent Samples)


ANOVA & Post Hoc Tests: Detect Statistically Significant Differences Among Group MeansAnalysis of variance (ANOVA): used when comparing the means

of three or more groups

Post hoc tests: options that are available to determine where the pair(s) of statistically significant differences between the means exist(s)Duncan’s multiple range test: provides output that is mostly

a “picture” of what means are significantly differentThe Duncan multiple range test’s output is much less

statistical than most other post hoc tests and is easy to interpret.


E6: Analysis of Variance


E7: Differences Between Two Means Within the Same Sample (Paired Sample)


The SPSS Chi-Square Analysis!Chi-square analysis: the examination of frequencies for two

nominal-scaled variables in a cross-tabulation table to determine whether the variables have a significant relationship

Assesses non-monotonic association in a cross-tabulation table based upon differences b/n observed and expected frequenciesFOR THIS ANALYSIS! The null hypothesis is that the 2

variables are NOT related/associated!Observed frequencies are the actual cell counts in the cross-

tabulation table.FOR THIS ANALYSIS! In order for the Hypothesis to hold we

are looking for a P value that is > to 0.05 (it means no association), if it is ≤ to 0.05 it means that there is association


E8: Chi-Square Analysis


The Correlation Coefficient (r)A correlation coefficient’s size indicates the strength of

association between two variables.The sign (+ or −) indicates the direction of the association.Regardless of its absolute value, the correlation coefficient

must be tested for statistical significance.For this test! the Sig. (2-tailed must be lower than 0.05)


E9: Identifying Correlation

Copyright © 2014 Pearson Education, Inc.12-1 SPSS Core Exam Guide for Spring 2014 The goal of this...

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