1.
This value indicates the probability that the null hypothesis is true and so it follows that a researcher would want a very small probability value in order to be able to claim that the test result is statistically significant.
2.
The 5% level of significance can also be written as........ (where p = the probability of the result occurring if the null hypothesis were true)
3.
When the 5% significance level is achieved in quantitative research, providing that the study has been carefully designed and executed, a more likely explanation is that the result is due to the effects of the manipulated independent variable.
A. 
The null hypothesis is, therefore, rejected.
B. 
The null hypothesis is, therefore, retained
4.
If the 5% level of significance or less is achieved (p < .05) this means that the probability of observing that particular result, if the null hypothesis is true, is.....
5.
A Type 1 error occurs when a null hypothesis......
A. 
Is rejected when it should have not been.
B. 
Is retained when it should not have been.
6.
A Type 2 error occurs when a null hypothesis......
A. 
Is retained when it should not have been.
B. 
Is rejected when it should have not been.
7.
In a statistical context, the term ‘population’ refers to a
A. 
Complete data set rather than to a sample (a subgroup) of the population.
B. 
Sample (a subgroup) of the population rather than to a complete data set
8.
The type of research design - The test you use will depend on whether the design of your experiment was independent or related (matched pairs or repeated measures) - Is a factor affecting the
A. 
Choice of Statistical Test
B. 
Choice of Sampling Method
9.
The type of data - The data will be measured on either a nominal, ordinal or ratio scale - Is a factor affecting the
A. 
Choice of Sampling Method
B. 
Choice of Statistical Test
10.
Data on this most basic scale of measurement simply involve distinguishing between different and mutually exclusive categories of a variable e.g. smokers/non-smokers.
11.
Can be organised into categories but these categories can also be placed in a logical order based on their meaning e.g. categories used to measure social class.
12.
Units of measurement that can be placed in a logical order and the intervals between adjacent units on the scale are equal because they are based on some standard unit of measurement e.g. the Celsius temperature scale.
13.
Measurements on a scale that has equal intervals and also a genuine zero-point e.g. height in centimeters or weight in kilograms.
14.
A test of statistical significance does not make any assumptions about the parameters (limits) underlying the distribution of the quantitative data.
15.
Is a test of difference that is suitable for comparing data gathered from two groups in an experiment using an independent group design. It can be used with ordinal data.
16.
If this value is equal to or less than the critical value for a given level of significance, the null hypothesis can be rejected - This applies to
17.
A test of difference, suitable for use with data gathered from an experiment, using a related (matched pairs or repeated measures) design. It can be used on ordinal data.
18.
If the observed value of T is equal to, or less than, the critical value for a given level of significance, the null hypothesis can be rejected - This applies to
19.
A test of correlation suitable for use with pairs of scores. It can be used with ordinal data.
A. 
Spearman's Correlation Coefficient
B. 
20.
If the observed value is equal to or greater than the critical value for a given level of significance, the null hypothesis can be rejected. This can be applied to
A. 
B. 
Spearman's Correlation Coefficient
21.
A test of association for use with data gathered from independent samples that are measured at a nominal level in the form of frequencies.
22.
If the observed value of x² is equal to or greater than the critical value for a given level of significance, the null hypothesis can be rejected. This applies to
A. 
Spearman's Correlation Coefficient
B. 
23.
A systematic research technique for analysing transcripts of interviews, documents or text (visual or written) including advertisements.
24.
A method for identifying, analyzing, and reporting patterns (themes) within data. It minimally organizes and describes your data set in detail.
It involves taking a body of text and organizing it into specific themes so that the content can be summarised.
25.
Involves approaching the data with no preconceptions about which themes might emerge.