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ByDr. Mojgan Afshari
Hypothesis Testing
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Descriptive statistics
Descriptive statistics are used to describe andsummarize the properties of the mass of data
collected from the respondents.
Measures of central tendency, such as meanand median, and dispersion, such as range andstandard deviation, are the main descriptivestatistics. Displays of data, such as histograms
and box-plots, are also considered techniquesof descriptive statistics.
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Inferential statistics
Inferential statistics are used to infer theproperties of the population from the
properties of the sample.
T-test, ANOVA, Chi-square, Spearman Rho,
Pearson PM Correlation, and Simple Linear
Regression are examples of inferentialstatistics.
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Population & Sample
The population must be defined explicitlybefore a sample is taken.
The bigger the sample, the more likely it is to
reflect the whole population.
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The basic requirement of inferential statistics isthe sample to be selected must be randomlychosen from the population. (A random sample
is one in which each individual in theprescribed population has an equal chance to
be included in the sample). Consequently,
findings from the sample can be generalized tothe population.
Sampling will determine how much and howwell the researcher may generalize his or her
findings. A bad sample may well render
findings meaningless.5
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THE MAJOR STATISTICAL
TECHNIQUES
Techniques used to explore differencesamong groups
Techniques used to explore relationshipsamong variables
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What factors determine the most
appropriate statistical techniques
1. Research objectives/ questions / purpose of
your study2. Measurement scales you used in your
research instrument
3. Research design of your studies4. Nature of your data ( meeting normality and /
or equality of variance assumptions for
parametric test)[Please see chapter 10 (Choosing the right statistic), Pallant, Julie, F.
(2007). SPSS Survival Manual: A Step by Step Guide to Data Analysis
Using SPSS for Windows.]7
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Suggested methods for data analysis based on
measurement scale and number of dependentand independent variables
Ordinal Ordinal
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Hypothesis Testing
Hypothesis refers to educated guess or assumption tobe tested
Hypothesis is formulated following the review ofrelated literature and prior to the execution of the study
Setting up and testing hypotheses is an essential partof statistical inference
Types of hypotheses:
1.Research hypothesis HA
2.Null hypothesis H0
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Characteristics of a Good Hypothesis
A major characteristic of a good research hypothesisis that it is consistent with previous research
A good hypothesis is a tentative, reasonableexplanation for the occurrence of certain behaviors,phenomena, or events
A good hypothesis states as clearly and concisely aspossible the expected relationship or difference
between two variables
A well-stated and defined hypothesis must be
testable
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Research Hypothesis HA
Also known as alternative hypothesis
A statement of what a statistical hypothesis testis set up to establish
In an experiment, the alternative hypothesismight be that the new teaching method has a
different effect, on average, compared to that ofthe current method
Or the alternative hypothesis might also be thatthe new method is better, on average, than the
current method
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Critical/
Rejection Region
Critical/
Rejection Region
Critical valueCritical value
Critical value is the value of the teststatistic that is needed to reject the
null hypothesis
The set of values of the teststatistic beyond the critical value is
called the critical or rejection region
Reject the null hypothesis if the value of the test statistic that fall beyond thecritical value and within the critical region.
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Reject H0: Calculated statistic > Critical value
Fail to reject H0: calculated statistic
Criticalvalue
Reject H0: Sig-value <
Fail to reject H0: Sig-value
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Assignment
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1. Describe the importance of descriptive and
inferential statistics in research?2. Which of the following is the highest type 1
error ? Explain why?
a. = .100b. = .01
c. =.001
d. =.0001
3. A researcher tested a hypothesis at the 0.05
significance level. Explain the meaning of thisstatement.
4. Explain factors that should be considered
before choosing a specific statisticalprocedure.28