Website traffic statistics, including Alexa Rank, engagement metrics, referral sources, and more for any site in our database. Audience insights, including sites that share an audience with your site, topics your audience cares most about, and keywords they search for 16 rows · Websitescoop is a free Website Analysis Tool which provides Website and Domain This page shows how to perform a number of statistical tests using SPSS. Each section gives a brief description of the aim of the statistical test, when it is used, an example showing the SPSS commands and SPSS (often abbreviated) output with a brief interpretation of the output. You can see the page Choosing the Correct Statistical Test for a table that shows an overview of
The Beginner's Guide to Statistical Analysis | 5 Steps & Examples
This page shows how to statistical analysis website a number of statistical tests using SPSS. Each section gives a brief description of the aim of the statistical test, when it is used, an example showing the SPSS commands and SPSS often abbreviated output with statistical analysis website brief interpretation of the output.
You can see the page Choosing the Correct Statistical Test for a table that shows an overview of when each test is appropriate to use, statistical analysis website. In deciding which test is appropriate to use, it is important to consider the type of variables that you have i. for more information on this, statistical analysis website. Most of the examples in this page will use a data file called hsb2, high school and beyond.
This data file contains observations from a sample of high school students with demographic information about the students, statistical analysis website, such statistical analysis website their gender femalesocio-economic status ses and ethnic background race.
It also contains a number of scores on standardized tests, including tests of reading readstatistical analysis website, writing writemathematics math and social studies socst.
You can get the hsb data file by clicking on hsb2. A one sample t-test allows us to test whether a sample mean of a normally distributed interval variable significantly differs from a hypothesized value.
For example, using the hsb2 data filesay we wish to test whether the average writing score write differs significantly from We can do this as shown below, statistical analysis website. The mean of the variable write for this particular sample of students is We would conclude that this group of students has a significantly higher mean on the writing test than A one sample median test allows us to test whether a sample median differs significantly from a hypothesized value, statistical analysis website.
We will use the same variable, statistical analysis website, writeas we did in the one sample t-test example above, statistical analysis website, but we do not need to assume that it is interval and normally distributed we only need to assume that write is an ordinal variable. A one sample binomial test allows us to test whether the proportion of successes on a two-level categorical dependent variable significantly differs from a hypothesized value.
A chi-square goodness of fit test allows us to test whether the observed proportions for a categorical variable differ from hypothesized proportions.
We want to test whether the observed proportions from our sample differ significantly from these hypothesized proportions. An independent samples t-test is used when you want to compare the means of a normally distributed interval dependent variable for two independent groups, statistical analysis website.
For example, using the hsb2 data filesay we wish to test whether the mean for write is the same for males and females. Because the standard deviations for the two groups are similar In other words, females have a statistically significantly higher mean score on writing The Wilcoxon-Mann-Whitney test is a non-parametric analog to the independent samples t-test and can be used when you do not assume that the dependent variable is a normally distributed interval variable you only assume that the variable is at least ordinal.
You will notice that the SPSS syntax for the Wilcoxon-Mann-Whitney test is almost identical to that of the independent samples t-test, statistical analysis website. We will use the same data file the hsb2 data file and the same variables in this example as we did in the independent t-test example above and will not assume that writeour dependent variable, is normally distributed. A chi-square test is used when you want to see if there is a relationship between two categorical variables.
In SPSS, the chisq option is used on the statistics subcommand of the crosstabs command to obtain the test statistic and its associated p-value, statistical analysis website. Remember that the chi-square test assumes that the expected value for each cell is five or higher. This assumption is easily met in the examples below. The point of this example is that one or both variables may have more than two levels, and that the variables do not have to have the same number of levels.
In this example, female has two levels male and female and ses has three levels low, statistical analysis website, medium and high. Please see the results from the chi squared example above, statistical analysis website. A one-way analysis of variance ANOVA is used when you have a categorical independent variable with two or more categories and a normally distributed interval dependent variable and you wish to test for differences in the means of the dependent variable broken down by the levels of the independent variable.
For example, using the hsb2 data filesay we wish to test whether the mean of write differs between the three program types prog.
The command for this test would be:. The mean of the dependent variable differs significantly among the levels of program type. However, we do not know if the difference is between only two of the levels or all three of the levels. The F test for the Model is the same as the F test for prog because prog was the only variable entered into the model.
If statistical analysis website variables had also been entered, the F test for the Model would have been different from prog. To see the mean of write for each level of program type. From this we can see statistical analysis website the students in the academic program have the highest mean statistical analysis website score, while students in the vocational program have the lowest. The Kruskal Wallis test is used when you have one independent variable with two or more levels and an statistical analysis website dependent variable.
In other words, it is the non-parametric version of ANOVA and a generalized form of the Mann-Whitney test method since it permits two or more groups. We will use the same data file as the one way ANOVA example above the hsb2 data file and the same variables as in the example above, but we will not assume that write is a statistical analysis website distributed interval variable, statistical analysis website.
If some of the scores receive statistical analysis website ranks, then a correction factor is used, yielding a slightly different value of chi-squared. With or without ties, statistical analysis website results indicate that there is a statistically significant difference among the three type of programs.
A paired samples t-test is used when you have two related observations i. For example, using the hsb2 data file we will test statistical analysis website the mean of read is equal to the mean of write, statistical analysis website. The Wilcoxon signed rank sum test is the non-parametric version of a paired samples t-test.
You use the Wilcoxon signed rank sum test when you do not wish to assume that the difference between the two variables is interval and normally distributed but you do assume the difference is ordinal. We will use the same example as above, but we will not assume that the difference between read and write is interval and normally distributed.
The results suggest that there is not a statistically significant difference between read and write. If you believe the differences between read and write were not ordinal but could merely be classified as positive and negative, then you may want to consider a sign test in lieu of sign rank test. Again, we will use the same variables in this example and assume that this difference is not ordinal.
These binary outcomes may be the same outcome variable on matched pairs like a case-control study or two outcome variables from a single group. Continuing with the hsb2 dataset used in several statistical analysis website examples, let us create two binary outcomes in our dataset: himath and hiread. These outcomes can be considered in a two-way contingency table. The null hypothesis is that the proportion of students in the himath group is the same as the proportion of students in hiread group i.
You would perform a one-way repeated measures analysis of variance if you had one categorical independent variable and a normally distributed interval dependent variable that was repeated at least twice for each subject. This is the equivalent of the paired samples t-test, but allows for two or more levels of the categorical variable. This tests whether the mean of the dependent variable differs by the categorical variable.
In this data set, y is the dependent variable, a is the repeated measure and s is the variable that indicates the subject number. You will notice that this output gives four different p-values. Because that assumption is often not valid, the three other p-values offer various corrections the Huynh-Feldt, H-F, Greenhouse-Geisser, G-G and Lower-bound.
No matter which p-value you use, our results indicate that we have a statistically significant effect of a at the. If you have a binary outcome measured repeatedly for each subject and you wish to run a statistical analysis website regression that accounts for the effect of multiple measures from single subjects, you can perform a repeated measures logistic regression.
In SPSS, this can be done using the GENLIN command and indicating binomial as the probability distribution and logit as the link function to be used in the model. The exercise data file contains 3 pulse measurements from each of 30 people assigned to 2 different diet regiments and 3 different exercise regiments. A factorial ANOVA has two or more categorical independent variables either with or without the interactions and a single normally distributed interval dependent variable.
For example, using the hsb2 data file we will look at writing scores write as the dependent variable and gender female and socio-economic status ses as independent variables, and we will include an interaction of female by ses.
Note that in SPSS, you do not need to have the interaction term s in your data set. You perform a Friedman statistical analysis website when you have one within-subjects independent variable with two or more levels and a dependent variable that is not interval and normally distributed but at least ordinal.
We will use this test to determine if there is a statistical analysis website in the reading, writing and math scores. The null hypothesis in this test is that the distribution of the ranks of each type of score i. To conduct a Friedman test, the data need to be in a long format. SPSS handles this for you, but in other statistical packages you will have to reshape the data before you can conduct this test.
Hence, there is no evidence that the distributions of the three types of scores are different. Ordered logistic regression is used when the dependent variable is ordered, but not continuous. For example, using the hsb2 data file we will create an ordered variable called write3. Statistical analysis website variable will have the values 1, 2 and 3, indicating a low, statistical analysis website, medium or high writing score. We do not generally recommend categorizing a continuous variable in this way; we are simply creating a variable to use for this example.
We will use gender femalereading score read and social studies score socst as predictor variables in this model. We will use a logit link and on the print subcommand we have requested the parameter estimates, the model summary statistics and the test of the parallel lines assumption.
There are two thresholds for this model because there are three levels of the outcome variable. One of the assumptions underlying ordinal logistic and ordinal probit regression is that the relationship between each pair of outcome groups is the same.
In other words, ordinal logistic regression assumes that the coefficients that describe the relationship between, say, the lowest versus all higher categories of the response variable are the same as those that describe statistical analysis website relationship between the next lowest category and all higher categories, etc.
This is called the proportional odds assumption or the parallel regression assumption. Because the relationship between all pairs of groups is the same, there is only one set of coefficients only one model. If this was not the case, we would need different models such as a generalized ordered logit model to describe the relationship between each pair of outcome groups.
A factorial logistic regression is used when you have two or more categorical independent variables but statistical analysis website dichotomous dependent variable, statistical analysis website. For example, using the hsb2 data file we will use female as our dependent variable, because it is the only dichotomous variable in our data set; certainly not because it common practice to use gender as an outcome variable.
We will use type of program prog and school type schtyp as our predictor variables. Because prog is a categorical variable it has three levelswe need to create dummy codes for it.
SPSS will do this for you by making dummy codes for all variables listed after the keyword with. SPSS will also create the interaction term; simply list the two variables that will make up the interaction separated by the keyword by.
Furthermore, none of the coefficients are statistically significant either, statistical analysis website. This shows that the overall effect of prog is not significant. A correlation is useful when you want to see the relationship between two or more normally distributed interval variables.
Statistical Tests: Choosing which statistical test to use
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