Interpreting spss output for ttests and anovas ftests. Demo of the most common hypothesis tests o now lets conduct the common hypothesis tests from the prior slides. If you are using t test, use the same formula for tstatistic and compare it now to tcritical for two tails. One sample hypothesis test of means or ttest of mean number of complaints per month.
This tutorial will show you how to use spss version 12. Strictly, most nonparametric tests in spss are distribution free tests. Suppose we want to test the claim that the population mean is larger than 35 or the mean score of 38. Because the hypothesis involves the phrase greater than, this must be a one tailed test. There are versions of spss for windows 98, 2000, me, nt, xp, major unix platforms solaris, linux, aix, and macintosh. Click here for online calculators that work well with summary statistics. Below is a sample data set that we will be using for todays exercise. Aug 20, 2014 the student will learn the big picture of what a hypothesis test is in statistics. My goal is to give you enough information to use spss to perform some different hypothesis tests.
Using spss for one sample tests spss isnt as good as stata for one sample tests. Statistics is a set of mathematical techniques used to summarize research data and determine whether the data supports a proposed hypothesis. The package is particularly useful for students and researchers in. Introduction to biostatistics 24pt hypothesis testing. Intro to hypothesis testing in statistics hypothesis. Test the hypothesis that the mean pollution indexes are the same for the two areas. See the further resources section for more information. There was not enough evidence to suggest a significant difference between the college gpas of the two groups of students, t38. For example, if you open an excel file it may ask which worksheet and whether or. My goal is to give you enough information to use spss to perform some different hypothesis tests without getting into the nitty gritty detail. Adding an unimportant predictor may increase the residual mean square thereby reducing the usefulness of the model.
In this section, we describe the four steps of hypothesis testing that were briefly introduced in section 8. Singlesinglesample sample ttests yhypothesis test in which we compare data from one sample to a population for which we know the mean but not the standard deviation. Spss output for one sample hypothesis test of means or ttests the purpose of this lecture is to illustrate the spss output for onesample hypothesis test of means or one sample ttests. To select variables, first click on a variable name in the box on the left side of the dialog box, then.
The standard hypothesis test will be run at a significance level of 5%, but if you did wish to change this you can click the options button and change this setting. Paired data 2 spss does this really well but you do need the raw data. We will discuss terms such as the null hypothesis, the alternate hypothesis, statistical significance of a. If the reader is familiar with this limited number of tests, heshe will be capable of interpreting a large pro. Twosample ttests in spss stat 314 the table below shows the observed pollution indexes of air samples in two areas of a city. The onesample t test procedure tests whether the mean of a single variable differs from a specified constant. Twosample hypothesis test of means some common sense assumptions for two sample hypothesis tests 1. Bartletts test of sphericity tests the hypothesis that your correlation matrix is an identity matrix, which would indicate that your variables are unrelated and therefore unsuitable for structure detection. We will present sample programs for some basic statistical tests in spss, including t tests, chi square, correlation, regression, and analysis of variance. The correlation coefficient is the slope of the regression line between two variables when both variables have been standardized. The test variable used is appropriate for a mean intervalratio level. We are still just calculating a test statistic to see if some hypothesis could have plausibly generated our data.
General statistics and hypothesis testing spss tutorial. Hypothesis testing or significance testing is a method for testing a claim or hypothesis about a parameter in a population, using data measured in a sample. Parametric and nonparametric tests parametric tests. Descriptive and inferential statistics 5 the department of statistics and data sciences, the university of texas at austin for anticipating further analyses. Hypothesis testing with t tests university of michigan. The following research hypothesis we are going to test out in this literature. The slope is given in the b column to the right of the name of the x variable. The method of hypothesis testing uses tests of signi.
The other hypothesis, which is assumed to be true when the null hypothesis is false, is referred to as the alternative hypothesis, and is often symbolized by ha or h1. The null hypothesis in levenes test is that the variances are equal. The form of the ttest is slightly different for the independent samples and dependent samples types of two sample tests, and spss has separate procedures for. Spss statistics includes tools that can be used to analyze variables and determine the strength and. For this example we are testing the following hypotheses in the two sample ttest. In this example, we get descriptive statistics for the older variable. Spss hypothesis testing and classical tests sample assignment hypothesis test. Inferentialstatisticsareusedtotesthypotheses abouttherelationshipbetweentheindependent andthedependentvariables. If that null hypothesis were true, then using the regression equation would be no better. It must be in the form of rowscases and columnsvariables. The table below shows the observed pollution indexes of air samples in two areas of a city. The main statistical end product of nhst is the p value, which is the most commonly encountered inferential statistic and most frequently misunderstood, misinterpreted, and misconstrued statistics in the biomedical and public health literature. The variables used for testing out the hypotheses include height, weight, age and gender of the respondents for which the data is collected. Statistical inference is the act of generalizing from sample the data to a larger phenomenon the.
According to the ttest, we failed to reject the null hypothesis. Lecture 5 hypothesis testing in multiple linear regression. It lists the heights for 10 men and 12 women collected at truman state university. Two proportion ztests in spss stat 314 in a test of the reliability of products produced by two machines, machine a produced 15 defective parts in a run of 280, while machine b produced 10 defective parts in a run of 200. In order to demonstrate how these commands handle missing values, some of. Similar to our approach for nding con dence intervals, we. Hypothesis testing the center for applied statistics and. Sample t test students t test is the one we have already seen in the example. The number of scores that are free to vary when estimating a population parameter from a sample df n 1 for a singlesample t test. Nonetheless, spss is probably adequate for most needs. It does not have anything like statas calculator functions, so you have to have raw data. Relies on theoretical distributions of the test statistic under the null hypothesis and assumptions about the distribution of the sample data i.
The independentsamples and pairedsamples t tests in spss. Introduction to null hypothesis significance testing. Specifically, we demonstrate procedures for running dependentsample or onesample ttests, independentsample ttests, differencesample or matched or pairedsample ttests. Both the null and alternative hypothesis should be stated before any statistical test of significance is conducted. Spss runs three tests when you request an independentsamples t test. Do these results imply a difference in the reliability of these two machines.
Hypothesis testing using ttests so far, we have assumed that the population variance. Hypothesis test difference 4 if you are using z test, use the same formula for zstatistic but compare it now to zcritical for two tails. First, select cases sex1 so that only the males are. Oddly, these two concepts are entirely different but often used interchangeably. Spss nonparametric tests are mostly used when assumptions arent met for other tests such as anova or t tests. Null hypothesis h0 a statistical hypothesis that states that there is no difference between a parameter and a specific value, or that there is no difference between two parameters. If the null hypothesis is rejected then we must accept that the alternative hypothesis is true. Cpspubfeb2000 this dataset is a subset of the current population survey basic monthly survey from february 2000. The following datasets will be used in this document. We tend to want to accept the alternative hypothesis. An overview of statistical tests in spss spss learning modules. Hypothesis testing santorico page 272 we tend to want to reject the null hypothesis so we assume it is true and look for enough evidence to conclude it is incorrect. More information is sometimes available in statas output.
For example, a population might be all the individuals that live in the united. Descriptive and inferential statistics 4 the department of statistics and data sciences, the university of texas at austin. T tests in spss stat 314 average systolic blood pressure of a normal male is supposed to be about 129. The null hypothesis usually re ects the \status quo or othing of interest.
Preface spss, standing for statistical package for the social sciences, is a powerful, userfriendly software package for the manipulation and statistical analysis of data. Spss does this really well but you do need the raw data. Measurements of systolic blood pressure on a sample of 12 adult males from a community whose dietary habits are suspected of causing high blood pressure are listed below. In this method, we test some hypothesis by determining the likelihood that a sample statistic could have been selected, if the hypothesis regarding the population parameter were true. The analyses reported in this book are based on spss version 11. Hypothesis testing santorico page 271 there are two types of statistical hypotheses. Independent data 4 spss does this really well but you do need the raw data1. In this book, we describe the most popular, spss for windows, although most features are shared by the other versions.
The first test is the levenes test for equality of variances the first two statistics boxes in the above table highlighted in yellow. To perform a one sample ttest click analyzecompare meansone. Lecture 5 hypothesis testing in multiple linear regression biost 515 january 20, 2004. The program below reads the data and creates a temporary spss data file. Spss 1sample ttest and 2sample ttests for independent and paired samples are demonstrated. That is up to the researcher to determine from the presented results. Exercise using spss to explore hypothesis testing independent.
If the null hypothesis is assumed to be true, what is the probability of obtaining the observed result, or any more extreme result that is favourable to the alternative hypothesis. A general rule of thumb is that we reject the null hypothesis if sig. In each problem considered, the question of interest is simpli ed into two competing hypothesis. Spss will not indicate whether the null hypothesis has been rejected. The data will be entered in the same way that it was in the spss introduction handout. Use spss to conduct a t test testing the null hypothesis that there is no. Referred to as distribution free as they do not assume that data are drawn from any particular. Hypothesis testing using z and t tests in hypothesis testing, one attempts to answer the following question. Can you make up some hypothesis about the population in 1. Spss can not be used with only the summarizing statistics mean, standard deviation, sample size. In addition to the height and gender columns, we will add another column hfemale. Exercise using spss to explore hypothesis testing ssric. In order to run an efficient test you will need to choose a sample that represents your. This article will accordingly discuss these tests and their proper application, together with other important statistical tests.
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