SPSS the Statistical Package for the Social Sciences

SPSS (the Statistical Package for the Social Sciences) PART 2

Lesson objectives o Recap SPSS n Data entry o o n o o Data view Variable view Descriptive analysis Determining reliability Inferential Statistics with SPSS

Inferential Statistics o o Based on the assumption that the sample is random Types of tests n n n Chi Squared Correlation T test

Example research Purpose : To determine if V-ROTAN method of teaching will lead to higher achievement and learning satisfaction among visual learners

Design Independent Variable Learning styles o o INTERVENTION Teaching method Dependent Variable Achievement Satisfaction Population: EDU Research student (100) Sample ( chosen at random, 3 lessons taught by the same person using the ‘method’) n n Class 1 (40) Class 2 (40)

Instruments o Learning style inventory n n o Questionnaire n n o Scores will determine learning styles Can categorize as visual, tactile or auditory Satisfaction regarding the teaching method higher score – higher lesson satisfaction Test n Scores will determine achievement

Establishing causality o o To establish causality, one must use an experimental or quasiexperimental design. True experimental designs include: n n n Pre-test/Post-test control group design Solomon Four-Group design Post-test only control group design

Threats in experimental research -Definite weakness + controlled ? Source of concern

What to describe? o Descriptive stats n n o Age Gender Program Learning styles Cross tabulate? n Gender and learning styles

Significance o o If significant, unlikely to have occurred by chance (kebetulan) there is statistical evidence that there is a difference, a correlation, an association between etc….

Probability of something happening? o Probability that you will die someday = _____?

Significance level o o o Significance levels show you how likely a result is due to chance. The most common level, used to mean something is good enough to be believed, is 0. 95 The finding has a 95% chance of being true. No statistical package will show you "95%" or ". 95" to indicate this level. Instead it will show you ". 05, " meaning that the finding has a five percent (. 05) chance of not being true, which is the converse of a 95% chance of being true. To find the significance level, subtract the number shown from one. For example, a value of ". 01" means that there is a 99% (1 -. 01=. 99) chance of it being true

Hypothesis testing o The Null hypothesis states there is no true difference/no relationship between parameters in the population n We reject or fail to reject the null hypothesis o o It is rejected only when it becomes evidently false, that is, when the researcher has a certain degree of confidence, usually 95% to 99%, that the data do not support the null hypothesis Example n There is no significant difference between the mean test scores of visual and tactile learners

Hypothesis testing o YOU ALWAYS TEST THE NULL HYPOTHESIS!

Significance o Test of significance n n To decide whether to reject the null hypothesis Select probability o o n 5 out of 100 times the difference did not occur by chance ( Significance level: 0. 05) 1 out of 100 times the difference did not occur by chance ( Significance level: 0. 01) Confidence level? o 95% or 99%

Example o Null hypothesis n o o Significance level : 0. 05 Test statistic n o There is no relationship between variables. . Probability value 0. 009 or Sig. 0. 009 (smaller than 0. 05) What does that mean? n n n very unlikely that there’s no relationship between the variables Variables not independent of each other REJECT Null hypothesis

Example o Null hypothesis n o o Significance level : 0. 01 Test statistic n o There is no relationship between variables. . Probability value 0. 12 or Sig. 0. 12(greater than 0. 01) What does this mean? n n n Higher likelihood that there’s no relationship between the variables Variables are independent of each other Fail to reject (accept? ) Null hypothesis

Let’s get on with inferential statistics

Now. . What to infer? o o o Independence/ Association Correlation Differences

Independence test –Chi squared o Chi squared test is used in situations where you have two categorical variables n n o Gender and employment sector Gender and learning styles Chi-square test of independence tests the null hypothesis that there is no association between the two variables

Example: Test for independence o Gender n n o Learning styles n n n o Female Male Visual Tactile Auditory Null Hypothesis: No association between gender and learning styles

Using SPSS for chi squared o Click n Analyze o Descriptive n Crosstabs o Statistics

Using SPSS for chi squared o o o Low chi squared statistic Sig. 961 Fail to reject the null hypothesis There is no association… Variables independent of each other

Correlation o o Measure of the linear relationship between two variables. A correlation coefficient has a value ranging from -1 to 1. Values that are closer to the absolute value of 1 indicate that there is a strong relationship between the variables being correlated whereas values closer to 0 indicate that there is little or no linear relationship. The sign of a correlation coefficient describes the type of relationship between the variables being correlated. n n A positive correlation coefficient indicates that there is a positive linear relationship between the variables: as one variable increases in value, so does the other. A negative value indicates a negative linear relationship between variables: as one variable increases in value, the other variable decreases in value.

Example: Correlation o o Correlation between learning styles and test scores Correlation between learning styles and satisfaction

Correlation in SPSS o o Start at the Analyze menu. Select the Correlate option from this menu. You will see three options for correlating variables: n n n o Bivariate Partial Distances. The bivariate correlation is for situations where you are interested only in the relationship between two variables

Correlation in SPSS o Then, consider is the type of correlation coefficient. n n o Pearson's is appropriate for continuous data Kendall's tau-b and Spearman's, are designed for ranked data. The choice between a one and two-tailed significance test in the Test of Significance box should be determined by the hypothesis you are testing n n if you are making a prediction that there is a negative or positive relationship between the variables, then the onetailed test is appropriate if you are not making a directional prediction, you should use the two-tailed test (there is not a specific prediction about the direction of the relationship between the variables)

Output

Output o Correlation is not statistically significant

Let’s check for significant difference Differences between test scores of the groups of learners

Differences: Using t test o The t test is a useful technique for comparing mean values of two sets of numbers. n o Statistic for evaluating whether the difference between two means is statistically significant. t tests can be used either n n to compare two independent groups (independent-samples t test) to compare observations from two measurement occasions for the same group (paired-samples t test).

Remember t test - tests the null hypothesis / that there is no difference …

t test o o If you are using the t test to compare two groups, the groups should be randomly drawn from normally distributed and independent populations. Using SPSS n Analyze o Compare Means One-Sample T test. . . Independent-Samples T test. . . Paired-Samples T test. . .

Types of t-test o The one-sample t test is used compare a single sample with a population value. n o The independent-sample t test is used to compare two groups' scores on the same variable. n o Example, a test could be conducted to compare the average test scores of U 5 C with a value that was known to represent the whole EDU 540 population. Example : Compare the test scores of U 5 C and PKPG to evaluate whethere is a difference in their scores. The paired-sample t test is used to compare the means of two variables within a single group. n Example, it could be used to see if there is a statistically significant difference between test 1 and test 2 among the members of U 5 C

Using SPSS : t test

Output o Notice the two parts of the output n n o Equal variances assumed Equal variance not assumed Which to use? n n Look at Levene’s test for equality of variance If small Sig. - groups have unequal variances

Output o o t-statistics is -6. 024 Sig. level : . 000 The significance level tells us that the probability that (there is no difference between visual and tactile learners) – the “NULL” is very small Hence, there is a significant difference in the test scores between visual and tactile learners

Have fun with SPSS! Proceed to Qualitative Analysis and Ethics in Research