An independent-samples t-test was used to determine whether there was a statistically significant mean difference in the salaries between the internship group and the no internship group. Ook al heb je een hekel aan SPSS; je zal er toch aan moeten geloven. We do this using the Harvard and APA styles. Finally, the cell under the column should show . We do this over the four sections that follow: (1) understanding descriptive statistics; (2) the independent-samples t-test results using an "estimation" approach (using 95% CI); (3) the independent-samples t-test results using a "Null Hypothesis Significance Testing" (NHST) approach (using p-values); and (4) effect size calculations after carrying out an independent-samples t-test. As previously stated, the sample mean difference is the best estimate of the population mean difference, but since we have just one study where we took a single sample from each of our two populations, we know that this estimate of the population mean difference in cholesterol concentration between participants in the diet group and exercise group will vary (i.e., it will not always be the same as in this study). As before, you can also provide a label for your independent variable in the column. This is important because we are using the independent-samples t-test to assess whether our sample data gives us reason to believe that we should accept the alternative hypothesis at a certain level of probability. After the students have taken the maths exam, their scores (between 0 and 100 marks) were recorded. The independent-samples t-test, also known as the independent t-test, independent-measures t-test, between-subjects t-test or unpaired t-test, is used to determine whether there is a difference between two independent, unrelated groups (e.g., undergraduate versus PhD students, athletes given supplement A versus athletes given supplement B, etc.) Difference between two INDEPENDENT GROUPS De t-test wordt gebruikt om: twee groepen met elkaar te vergelijken (Independent samples t-test) één groep op 2 momenten te vergelijken (Paired samples t-test) An unstandardised effect size is reported using the units of measurement of the dependent variable. Therefore, the second column, , reflects our dichotomous independent variable, Intervention, since this was the second variable we entered into the Variable View window. Dat is bij een Sig. Note: If the button is not active (i.e., it looks faded, like this ), click into the Grouping Variable: box to make sure that the independent variable (e.g., in our example, Intervention) is highlighted in yellow, as it is in Step 2 above. De SPSS-output voor de independent samples t-test (t-test voor onafhankelijke steekproeven) bevat twee tabellen. The researcher analysed the data collected to determine whether the exam results were better (or worse) amongst students in the experimental group compared to the control group. Kang, Y., & Harring, J. R. (2012). The One-Sample T Test window opens where you will specify the variables to be used in the analysis. In this introductory guide to the independent-samples t-test, we first describe two study designs where the independent-samples t-test is most often used, before explaining why an independent-samples t-test is being carried out to analyse your data rather than simply using descriptive statistics. In the Independent Samples Test table above, the obtained t-value is 3.06 (to 2 decimal places), reported under the "t" column, and the degrees of freedom (df) are 38, reported under the "df" column (i.e., for an independent-samples t-test with equal variances, the degrees of freedom are equal to the sample size minus 2, so in our example, 40 – 2 = 38). The results show that the mean cholesterol concentration in the diet group was 6.32 mmol/L (to 2 decimal places) with a standard deviation of 0.58 mmol/L (again reported to 2 decimal places). This group of 30 graduates represented the "no internship group". Since assumptions #1, #2 and #3 relate to your study design and how you measured your variables, if any of these three assumptions are not met (i.e., if any of these assumptions do not fit with your research), the independent-samples t-test is the incorrect statistical test to analyse your data. Note: The way that you analyse your data using an independent-samples t-test is the same when your dichotomous independent variable is a nominal variable or an ordinal variable. For example, you may want to test to determine if there is a difference between the cholesterol levels of men and women. You have now successfully entered all the information that SPSS Statistics needs to know about your dependent variable and independent variable into the Variable View window. We suggest that you do because there are certain analyses in SPSS Statistics where the setting results in your variables being automatically transferred into certain fields of the dialogue boxes you are using. In the next section, we show you how to carry out an independent-samples t-test using SPSS Statistics. For example, imagine that we randomly selected 150 male and 150 female university students in the United States to form our two samples. Join the 10,000s of students, academics and professionals who rely on Laerd Statistics. This is the next box you will look at. Perlu kita pahami bersama bahwa dalam statistik parametrik terdapat syarat-syarat yang harus terpenuhi sebelum kita dapat melakukan pengujian hipotesis (dalam hal ini uji hipotesis menggunakan uji independent sample t-test). To determine which intervention – the diet intervention or the exercise intervention – was most effective in improving cardiovascular health (i.e., by lowering participants' cholesterol concentrations), the researcher carried out an independent-samples t-test to: Using the results from the independent-samples t-test, the researcher then: Explanation: As explain in the earlier section, Understanding why the independent-samples t-test is being used, the independent-samples t-test: (a) using the NHST approach, gives you an idea of whether there is a mean difference between your two groups in the population, based on your sample data; and (b) as a method of estimation using confidence intervals (CI), provides a plausible range of values that the mean difference between your two groups could be in the population, based on your sample data. To carry out an independent-samples t-test, you have to set up two variables in SPSS Statistics. After carrying out an independent-samples t-test in the previous section, SPSS Statistics displays the results in the IBM SPSS Statistics Viewer using two tables: the Group Statistics table and the Independent Samples Test table. © 2021 - Statistiekbegeleider. This experimental group was called the "exercise" group. In the other group, the school children are not offered anything, irrespective of how well they performed in the same maths exam. In order to quantify this uncertainty in our estimate of the population mean difference, we can use the independent-samples t-test to provide a 95% confidence interval (CI), which is a way of providing a measure of this uncertainty. Based on the file setup for the dependent variable and independent variable in the Variable View above, the Data View window should look as follows: Note: On the left above, the responses for our independent variable are shown in text (e.g., "Diet" and "Exercise" under the column). Presenting a mean difference with a 95% CI to understand what the population mean difference is, and your uncertainty in its value, is an approach called "estimation". By clicking on the button the coding will appear in the main box (e.g., "1.00 = "Diet" for Intervention). Wat als je er niet uitkomt met de output independent samples t-test? However, in this introductory guide to the independent-samples t-test, we explain how to interpret your results when your data "passed/met" assumptions #4, #5 and #6. SPSS provides the mean difference between the two groups and the standarddeviation, sta… Therefore, imagine that a researcher wanted to determine whether students who enrolled in a 3-year degree course that included a mandatory 1-year internship (also known as a placement) received better graduate salaries than students who did not undertake an internship. We'll get to the other 3 dependent variables later. A critical evaluation of four anaesthesia journals. Nonetheless, when carrying out an independent-samples t-test, it is common to interpret and report both the p-value and 95% CI. These descriptive statistics have the following meaning: The sample mean (i.e., the "average" score) for each group of the independent variable, which is the measure of central tendency used in an independent-samples t-test. These eight steps are the same for SPSS Statistics versions 18 to 26, where version 26 is the latest version of SPSS Statistics. You can toggle between these two views of your data by clicking the "Value Labels" icon () in the main toolbar. Output tabellen van de independent t-test, Interpreteren output independent samples t-test. However, it is rarely possible to study the whole population (i.e., imagine the time and cost involved in collecting data on weekly screen time for the millions of university students in the United States). As an introduction to effect size measures, these can be classified into two categories: unstandardised and standardised. The researcher was specifically interested in students who undertook a Finance degree. In the Procedure section, we set out the simple 8-step procedure in SPSS Statistics to carry out an independent-samples t-test, including useful descriptive statistics. When checking if your data meets these three assumptions, do not be surprised if this process takes up the majority of the time you dedicate to carrying out your analysis. It is important to note that you cannot accept the null hypothesis that there is no mean difference. We could then simply compare the mean difference in weekly screen time between all male and all female students using descriptive statistics to understand whether there was a difference. Alternatively, you could use an independent-samples t-test to understand whether there is a mean (average) difference in weight loss between obese patients who undergo a 12-week exercise programme compared to obese patients who are given dieting pills (appetite suppressors) by their doctor. Presented at the annual meeting of the American Educational Research Association (AERA), SIG: Educational Statisticians, Vancouver, BC. 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. Instead, we are using the default settings because: (a) we want to test the statistical significance of the mean difference between our two groups using an alpha level (α) of .05; (b) we want SPSS Statistics to report the 95% CI of the mean difference; and (c) we are carrying out only one independent-samples t-test (and have no missing data). In other words, the mean difference in this "amount" of cholesterol concentration suggests that the effect of a 6-month exercise programme compared to 6-month dietary programme is worthy of further research. At the end of the 6-month study, the results showed that cholesterol concentration was lower in the exercise group (5.81 ± 0.48 mmol/L) compared to the diet group (6.32 ± 0.58 mmol/L), a mean difference of 0.52 (95% CI, 0.17 to 0.86) mmol/L, t(38) = 3.06, p = .004. Of a continuous dependent variable have population samples from two ethnic groups that you can toggle these. Hypothese moeten verwerpen en de HA variable in the previous section,,. Weight loss can reduce cholesterol concentration of 3.57 mmol/L would be to find out the effect of a,..., to continue with this introductory guide these terms t-test hebt uitgevoerd ( nul hypothese moeten en. 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