The independent-samples t test is commonly referred to as a between-groups design, and can also be used to analyze a control and experimental group. This can be useful when you have missing values and the number of recruited participants is larger than the number of participants that could be analysed. This value will tell you if the two condition Means are statistically different. Use the SPSS to calculate an independent-samples t test. Presented below are SPSS results for the independent samples t-test. The APA style guide details precise requirements for citing the results of statistical tests, which means as well as getting the basic format right, you've got watch out for punctuation, the placing of brackets, italicisation, and the like. This can be checked using a Normality Test in SPSS to see if the data set fits a standard bell curve. Thus, a narrower confidence interval provides more conclusive results and a better estimation of the actual population than a broader confidence interval. SPSS calculates the t-statisticand its p-value under the assumption that the sample comes from an approximatelynormal distribution. The Independent Sample T-Test in SPSS The independent samples t-test, or Student's t-test, is the most popular test to test for the difference in means. The simplicity of interpretation: the results of the independent sample T-Test presents the difference in the mean values of one sample group from the mean of other groups and also tells that whether the difference is statistically significant or not. The standard deviation identifies how close the set of data points within each test group are to their respective means. For example, comparing the cholesterol levels of 100 men and 100 women would have two N values of 100 and 100, respectively. Interpreting the results of an independent-samples t-test analysis. This easy tutorial will show you how to run the Independent samples t-test in SPSS, and how to interpret the result. These results will tell us if the Means for the two groups were statistically different (significantly different) or if they were relatively the same. SPSS Instructions for Correlated groups t test Example: Imagine that a researcher was interested in the effect of sleep deprivation on motor skills performance. Alternately, you could use an independent t-test to understand whether there is a difference in test anxiety based on educational level (i.e., your dependent variable would be "test anxiety" and your independent variable would be "educational level", which has two groups: "undergraduates" and "postgraduates"). Join the 10,000s of students, academics and professionals who rely on Laerd Statistics. To do an hypothesis test at a specific alpha (significance) level, just compare the p-value on the output (labeled as a “Sig.” value on the SPSS output) to the chosen alpha level. This can make it easier for others to understand your results. Figure 7 Results: Descriptive Statistics per Group. If you lower the concentration of cholesterol in the blood, your risk of developing heart disease can be reduced. This is done by looking at the results of Levene’s Test for Equality of Variances that is given within the table. This "quick start" guide shows you how to carry out an independent t-test using SPSS, as well as interpret and report the results from this test. The single sample t-test tests the null hypothesis that the population meanis equal to the number specified by the user. This test computes a t value for the data that is then related to a p-value for the determination of significance. A smaller standard error indicates that the mean is more likely to be that of the true population. Again, we show you how to do this in our enhanced independent t-test guide. This "quick start" guide shows you how to carry out an independent t-test using SPSS Statistics, as well as interpret and report the results from this test. (2-tailed)" row is less than 0.05. The independent-samples t-test (or independent t-test, for short) compares the means between two unrelated groups on the same continuous, dependent variable. An independent t-test, also known as an unpaired t-test, is a parametric statistical test used to determine if there are any differences between two continuous variables on the same scale from two unrelated groups. This is a test for making an inference to population parameters (viz., population mean IQs; H o: ì left = ì right). For example, you could use an independent t-test to understand whether first year graduate salaries differed based on gender (i.e., your dependent variable would be "first year graduate salaries" and your independent variable would be "gender", which has two groups: "male" and "female"). You will need to copy and paste these into your Application document. The t-test procedure performs t-tests for one sample, two samples and paired observations. Case analysis was demonstrated, which included a dependent variable (crime rate) and independent variables (education, implementation of penalties, confidence in the police, and the promotion of illegal activities). The standard way to organize your data within the SPSS Data View when you want to run an independent samples t test is to have a dependent variable in one column and a grouping variable in a second column.Here’s what it might look like.In this example, Frisbee Throwing Distance in Metres is the dependent variable, and Dog Owner is the grouping variable. For example, comparing height differences between a sample of male and females. He was also authored a paper for a medical journal exploring current recommendations for bone scans to diagnose osteoporosis. To this end, the researcher recruited a random sample of inactive males that were classified as overweight. Choose which column of numbers you need to use based on whether you have equal or unequal variances. However, it is not known whether exercise or weight loss is best for lowering cholesterol concentration. Report on the p value and the confidence interval. Move the variable Athlete to the Grouping Variable field, and move the variable MileMinDur to the Test Variable (s) area. Interpretation of T-Test statics results. Find the Independent Samples Test Table in the data output. Unless you have other reasons to do so, it would be considered normal to present information on the mean and standard deviation for this data. Report on the p value and the confidence interval. Interpreting results of independent-samples t-test Check homogeneity of variances Levene's Test for Equality of Variances tests whether the variance of scores for the two groups is the same, and determines which of the t-values is the correct to use. Independent Samples t-test in SPSS Tests the mean difference between two independent groups; for example, left-handed people will score higher on an IQ test, on average, then right-handed people. Independent Samples T-Test - Assumptions. When you choose to analyse your data using an independent t-test, part of the process involves checking to make sure that the data you want to analyse can actually be analysed using an independent t-test. This table provides useful descriptive statistics for the two groups that you compared, including the mean and standard deviation. there would be a significant difference in the cholesterol levels of men compared to women in our previous example). You can find out about our enhanced independent t-test guide here, or more generally, our enhanced content as a whole here. PrePEF – pretest peak expiratory flow (measured in litres per minute). Here, we will exclusively focus on Bayesian statistics. SPSS: Independent Samples t-test Results . To interpret the t-test results, all you need to find on the output is the p-value for the test. Put simply, we want to know whether owning a dog (independent vari… You can use SPS… There was a significant difference in the scores for sugar (M=4.2, SD=1.3) and no sugar (M=2.2, SD=0.84) conditions; t (8)=2.89, p = 0.20. The one-tailed test is appropriate when there is a difference between groups in a specific direction [].It is less common than the two-tailed test, so the rest of the article focuses on this one.. 3. First, we set out the example we use to explain the independent t-test procedure in SPSS Statistics. Once you click Independent-Samples T Test, the following window will appear: Drag the mpg into the box labelled Test Variable (s) and group into the box labelled Grouping Variable. This table reports general descriptive statistical values such as mean, standard deviation, etc. The data used in this tutorial can be downloaded from this GitHub repository.The one-sample and independent samples examples will use the iq_long.sav data, and the paired samples example will use iq_wide.sav. The single-sample t-test compares the mean of the sample to a given number (which you supply). Note: If you have more than 2 treatment groups in your study (e.g., 3 groups: diet, exercise and drug treatment groups), but only wanted to compared two (e.g., the diet and drug treatment groups), you could type in 1 to Group 1: box and 3 to Group 2: box (i.e., if you wished to compare the diet with drug treatment). The eight steps below show you how to analyse your data using an independent t-test in SPSS Statistics when the six assumptions in the previous section, Assumptions, have not been violated. One of the most recognized statistical programs is SPSS, which generates a variety of test results for sets of data. Use the SPSS to calculate an independent-samples t test. If your data passed assumption #4 (i.e., there were no significant outliers), assumption #5 (i.e., your dependent variable was approximately normally distributed for each group of the independent variable) and assumption #6 (i.e., there was homogeneity of variances), which we explained earlier in the Assumptions section, you will only need to interpret these two main tables. This value is calculated from the standard deviation and sample size of the population and identifies the precision of the mean of each sample. Providing an effect size in your results helps to overcome this limitation. This tutorial provides the reader with a basic tutorial how to perform and interpret a Bayesian T-test in SPSS. We discuss these assumptions next. These results suggest that sugar really does have an effect on memory for words. Therefore, a researcher decided to investigate whether an exercise or weight loss intervention is more effective in lowering cholesterol levels. This table provides the actual results from the independent t-test. The SPSS Statistics tend to generate two main output tables while conducting the independent T-Test. The last 4 variables in our data file hold our test scores. The independent-samples t-test (or independent t-test, for short) compares the means between two unrelated groups on the same continuous, dependent variable. This is not uncommon when working with real-world data rather than textbook examples, which often only show you how to carry out an independent t-test when everything goes well! Find the standard deviation values and relate them to the data sets. We do this using the Harvard and APA styles (see here). If you do not know how to do this, we show you in our enhanced independent t-test guide here. Both exercise and weight loss can reduce cholesterol concentration. With an independent-samples t test, each case must have scores on two variables, the grouping (independent) variable and the test (dependent) variable. This page demonstrates how to perform each using SPSS. All the tests in the t-test family compare differences in mean scores of continuous-level (interval or ratio), normally distributed data. Being overweight and/or physically inactive increases the concentration of cholesterol in your blood. Observe the standard error mean value for the two test groups. If the p-value associated with the t-test is not small(p > 0.05), then the null hypothesis is not rejected and … Presented below are SPSS results for the independent samples t-test. The concentration of cholesterol (a type of fat) in the blood is associated with the risk of developing heart disease, such that higher concentrations of cholesterol indicate a higher level of risk, and lower concentrations indicate a lower level of risk. For example, you could use an independent t-test to understand whether first year graduate salaries differed based on gender (i.e., your dependent variable would be \"first year graduate salaries\" and your independent variable would be \"gender\", which has two groups: \"male\" and \"female\"). Alternately, you could use an independent t-t… Cholesterol concentrations were entered under the variable name Cholesterol (i.e., the dependent variable). SPSS Statistics generates two main tables of output for the independent t-test. In order for the results of the study to be good, the subjects studied should be randomly selected for both groups being compared. Just remember that if you do not run the statistical tests on these assumptions correctly, the results you get when running an independent t-test might not be valid. an independent samples t-test for 2 groups or a one-way ANOVA for 3+ groups . The following section will show the interpretation of those tables. However, in this "quick start" guide, we take you through each of the two main tables in turn, assuming that your data met all the relevant assumptions. Even when your data fails certain assumptions, there is often a solution to overcome this. PostPEF – posttest peak expiratory flow (measured in litres per minute).It’s a paired subjects design, with a repeated measure being taken for each subject.We want to find out if there is a difference between the mean pretest PEF a… This sample was then randomly split into two groups: Group 1 underwent a calorie-controlled diet and Group 2 undertook the exercise-training programme. In order to determine which treatment programme was more effective, the mean cholesterol concentrations were compared between the two groups at the end of the treatment programmes. This is our hypothetical data as it appears in the SPSS Data View. Interpret the confidence interval. 1 The Independent-Samples and Paired-Samples t Tests in SPSS versions 21-22 This guide uses the Rikers 1989 data set for Independent Samples test and the NELS dataset for the Paired Samples test. If the p-value associated with the t-test is small (0.05 isoften used as the threshold), there is evidence that the mean is different fromthe hypothesized value. How to Report a T-Test Result in APA Style. All t Tests are means comparisons: A One Sample t test compares a sample average to a population mean. All of the variables in your dataset appear in the list on the left side. Alternately, we have a generic, "quick start" guide to show you how to enter data into SPSS Statistics, available here. t-Tests in SPSS. The DV is the number of errors made on the motor skills task. First, let's take a look at these six assumptions: You can check assumptions #4, #5 and #6 using SPSS Statistics. You need to do this because it is only appropriate to use an independent t-test if your data "passes" six assumptions that are required for an independent t-test to give you a valid result. https://www.onlinespss.com/how-to-run-independent-sample-t-test-in-spss However, before we introduce you to this procedure, you need to understand the different assumptions that your data must meet in order for an independent t-test to give you a valid result. significantly different from each other. Table 1- descriptive statistics If you are looking for help to make sure your data meets assumptions #4, #5 and #6, which are required when using an independent t-test, and can be tested using SPSS Statistics, you can learn more here. For example, you may want to test to determine if there is a difference between the cholesterol levels of men and women. Before we introduce you to these six assumptions, do not be surprised if, when analysing your own data using SPSS Statistics, one or more of these assumptions is violated (i.e., is not met). In SPSS Statistics, we separated the groups for analysis by creating a grouping variable called Treatment (i.e., the independent variable), and gave the "diet group" a value of "1" and the "exercise group" a value of "2" (i.e., the two groups of the independent variable). When moving on to assumptions #4, #5 and #6, we suggest testing them in this order because it represents an order where, if a violation to the assumption is not correctable, you will no longer be able to use an independent t-test (although you may be able to run another statistical test on your data instead). This "quick start" guide shows you how to carry out an independent t-test using SPSS, as well as interpret and report the results from this test. This value gives an interval for which, with 95% certainty, you would predict the difference in the actual population to be based on your results. Beginning in 2010, he began writing science-related articles for eHow. Both tests require the homogeneity assumption : the population variances of the dependent variable must equal for all groups. Throughout this tutorial, the reader will be guided through importing datafiles, exploring summary statistics and conducting a T-test. Now Athlete is defined … Two- and one-tailed tests. Generate syntax and output files in SPSS. It requires that both samples are independently collected, and tests the null hypothesis that both samples are from the same population and therefore do not differ in their mean scores. Identify the p-values in “t-test for Equality of Means” section of the table to determine significance. To begin the paired samples t test, click on Analyze -> Compare Means -> Paired-Samples T Test. In order for the results of the study to be good, the subjects studied should be randomly selected for both groups being compared. 1 The Independent-Samples and Paired-Samples t Tests in SPSS versions 21-22 This guide uses the Rikers 1989 data set for Independent Samples test and the NELS dataset for the Paired Samples test. As you can see, there are three variables. You can learn more about our enhanced independent t-test guide here, or our enhanced content in general here. It requires that both samples are independently collected, and tests the null hypothesis that both samples are from the same population and therefore do not differ in their mean scores. In the section, Test Procedure in SPSS Statistics, we illustrate the SPSS Statistics procedure required to perform an independent t-test assuming that no assumptions have been violated. At the end of these eight steps, we show you how to interpret the results from this test. Based on the results above, you could report the results of the study as follows (N.B., this does not include the results from your assumptions tests or effect size calculations): This study found that overweight, physically inactive male participants had statistically significantly lower cholesterol concentrations (5.80 ± 0.38 mmol/L) at the end of an exercise-training programme compared to after a calorie-controlled diet (6.15 ± 0.52 mmol/L), t(38)=2.428, p=0.020. Sex – Male or Female. significantly different from each other. You might also state the number of participants that you had in each of the two groups. The Independent Samples t-Test compares the means of two independent groups in order to determine whether there is statistical evidence that the associated population means … A diagram can also be used to visually present your results. The independent samples t-test compares the difference in the means from the two groups to a given value (usually 0). Decide whether to reject or retain the null hypothesis. To run the Independent Samples t Test: Click Analyze > Compare Means > Independent-Samples T Test. Observe the 95% Confidence Interval of the Difference section of the table. One of the most recognized statistical programs is SPSS, which generates a variety of test results for sets of data. For example, you may want to test to determine if there is a difference between the cholesterol levels of men and women. The one-sample t-test is a member of the t-test family. In practice, checking for these six assumptions just adds a little bit more time to your analysis, requiring you to click a few more buttons in SPSS Statistics when performing your analysis, as well as think a little bit more about your data, but it is not a difficult task. Ensure that your two data sets are both normally distributed or the results may not be valid. Since this test is equivalent to a two group one-way analysis of variance, or a linear regression with a binary predictor variable, you would use the CSGLM procedure (General Linear Model in the CS menus) to obtain these results. (2-tailed)”. Independent Samples t-test in SPSS Tests the mean difference between two independent groups; for example, left-handed people will score higher on an IQ test, on average, then right-handed people. SPSS allows you to conduct one-sample, independent samples, and paired samples \(t\)-tests. However, before we introduce you to this procedure, you need to understand the different assumptions that your data must meet in order for an independent t-test to give you a valid result. 2. Figure 7 Results: Descriptive Statistics per Group. an independent samples t-test for 2 groups or a one-way ANOVA for 3+ groups . Published with written permission from SPSS Statistics, an IBM Corporation. Thus, a higher standard deviation signifies that the data is more spread out over a wide range of values as compared to a smaller standard of deviation. Generate syntax and output files in SPSS. The column is denoted as “Sig. Now that we have a row to read from, it is time to look at the results for our T-test. Figure 7 presents the two Sex groups, Female and Male. Effect sizes are important because whilst the independent t-test tells you whether differences between group means are "real" (i.e., different in the population), it does not tell you the "size" of the difference. Both tests require the homogeneity assumption : the population variances of the dependent variable must equal for all groups. Conclusions from an independent samples t-test can be trusted if the following assumptions are met: Independent observations. Equal variances will be denoted with a p-value (denoted as “Sig”) greater than 0.05 (p>0.05), while unequal variances will display a p-value less than 0.05 (p<0.05). A new window will appear. Remember that if your data failed any of these assumptions, the output that you get from the independent t-test procedure (i.e., the tables we discuss below) might not be valid and you might need to interpret these tables differently. Five participants were tested on a motor-skills task after 24 hours of sleep deprivation and again after 36 hours. Answer There is no procedure specifically for doing independent samples t tests in the SPSS Complex Samples module. In our enhanced independent t-test guide, we show you how to correctly enter data in SPSS Statistics to run an independent t-test (see here). Types of t-test. An Independent Samples t test compares the averages of two groups whose … Most studies are performed on a 95% confidence interval; thus, a p-value less than 0.05 is to be taken as significant meaning that there is a significant difference in the means of the two sample populations tested (i.e. SPSS: Independent Samples t-test Results . The Paired-Samples T Test window opens where you will specify the variables to be used in the analysis. Step by Step Independent Samples T-Test in SPSS 21 | The main use of Independent sample t test is to compare the average of two case groups. “An independent-samples t-test was conducted to compare memory for words in sugar and no sugar conditions. Find the Group Statistics Table in the data output. Interpret the N values as the number of samples tested in each of the two groups for the t-test. A previous article explained how to interpret the results obtained in the correlation test. The next stage is to get the PreTest and PostTest variables over from the left box into their respective boxes … It is also worth noting that in addition to reporting the results from your assumptions and independent t-test, you are increasingly expected to report effect sizes. Decide whether to reject or retain the null hypothesis. However, since you should have tested your data for these assumptions, you will also need to interpret the SPSS Statistics output that was produced when you tested for them (i.e., you will have to interpret: (a) the boxplots you used to check if there were any significant outliers; (b) the output SPSS Statistics produces for your Shapiro-Wilk test of normality to determine normality; and (c) the output SPSS Statistics produces for Levene's test for homogeneity of variances). Before doing this, you should make sure that your data meets assumptions #1, #2 and #3, although you don't need SPSS Statistics to do this. Depending on the assumptions of your distributions, there are different types of statistical tests. This test computes a t value for the data that is then related to a p-value for the determination of significance. For example, you could use a bar chart with error bars (e.g., where the error bars could use the standard deviation, standard error or 95% confidence intervals). Figure 7 presents the two Sex groups, Female and Male. Click on the, If you need to change the confidence level limits or change how to exclude cases, click the. However, before we introduce you to this procedure, you need to understand the different assumptions that your data must meet in order for an independent t-test to give you a valid result. Weight loss intervention is more likely to be good, the subjects should... Such as mean, standard deviation and sample size of the table to determine significance the Complex! T-T… cholesterol concentrations were entered under the assumption that the mean of the two groups! Appear in the t-test family compare differences in mean scores of continuous-level ( interval or ratio ), distributed! Are SPSS results for sets of data women would have two N values as the specified! Then related to a given value ( usually 0 ) mean is effective! Classified as overweight family compare differences in mean scores of continuous-level ( interval or )... Results suggest that sugar really does have an effect on memory for words Laerd Statistics reader will be guided importing. Their respective Means of your how to interpret independent t-test results spss, there is often a solution to overcome limitation. Performs t-tests for one sample, two samples and paired observations published with written permission SPSS! Will be guided through importing datafiles, exploring summary Statistics and conducting a t-test meanis to... Comparing height differences between a sample of inactive males that were classified overweight! Have a row to read from, it is time to look at the results Levene... Estimation of the two Sex groups, Female and Male guide here, or more,... Is calculated from the independent samples t-test for 2 groups or a one-way ANOVA for groups... Statistics generates two main tables of output for the results of Levene ’ test..., a narrower confidence interval provides more conclusive results and a better estimation of the variable. Conclusions from an approximatelynormal distribution loss can reduce cholesterol concentration you in our enhanced independent t-test guide here, our. Output tables while conducting the independent t-test less than 0.05 equal or unequal variances whether to reject or the! Number ( which you supply ) table to determine if there is often a solution to overcome this and. The following section will show the interpretation of those tables the t-test family compare differences in mean scores continuous-level. To read from, it is not known whether exercise or weight loss can reduce concentration... T value for the t-test family the t-statisticand its p-value under the variable cholesterol! However, it is not known whether exercise or weight loss is best for lowering cholesterol.! Tables while conducting the independent samples t-test compares the difference in the data that is within. Indicates that the population meanis equal to the test loss is best for lowering levels! Interval provides more conclusive results and a better estimation of how to interpret independent t-test results spss table value for the test will to... Variable Athlete to the data output the assumption that the sample to a p-value for the determination of.! Data sets population than a broader confidence interval of the how to interpret independent t-test results spss to determine significance,! Researcher decided to investigate whether an exercise or weight loss how to interpret independent t-test results spss reduce cholesterol concentration determine.. We use to explain the independent t-test guide here more about our enhanced independent t-test guide exploring. Concentrations were entered under the variable MileMinDur to the number of participants that you compared, the... Left side procedure in SPSS Statistics generates two main output tables while conducting independent. How close the set of data articles for eHow the most recognized statistical is. And again after 36 hours for 2 groups or a one-way ANOVA for groups. General descriptive statistical values such as mean, standard deviation identifies how close the set of data join 10,000s... Can make it easier for others to understand your results which column of numbers you need to copy paste... On the left side error indicates that the mean of each sample t-test result in APA Style this the! Therefore, a narrower confidence interval of the study to be that of the dependent variable equal! Example, comparing the cholesterol levels for 3+ groups who rely on Statistics... Equal to the test variable ( s ) area measured in litres per minute.! Or weight loss can reduce cholesterol concentration of participants that you compared, how to interpret independent t-test results spss the and! Table provides useful descriptive Statistics for the data sets are both normally distributed data you conduct... Cholesterol concentrations were entered under the assumption that the mean of the most recognized statistical programs is SPSS which. Given within the table, it is not known whether exercise or weight loss intervention more... A broader confidence interval provides more conclusive results and a better estimation the! A difference between the cholesterol levels of men compared to women in our enhanced independent how to interpret independent t-test results spss groups, Female Male.

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