# SPSS 17 TUTORIAL PDF

The SPSS Statistics Brief Guide provides a set of tutorials designed to acquaint Reading Data. Figure Database Wizard Welcome dialog box. Examples using the statistical procedures found in SPSS Statistics Base . The SPSS Guide to Data Analysis for SPSS Statistics is also in. A guide to quantitative methods Almquist, Ashir & Brännström . PRODUCING DESCRIPTIVE STATISTICS IN SPSS. INTERACTION ANALYSIS. Author: ADRIANA YAKLICH Language: English, Dutch, Arabic Country: Maldives Genre: Business & Career Pages: 116 Published (Last): 08.07.2016 ISBN: 163-6-27414-560-1 ePub File Size: 28.35 MB PDF File Size: 9.43 MB Distribution: Free* [*Register to download] Downloads: 31787 Uploaded by: STEPHANIE There are six different windows that can be opened when using SPSS. .. ➢ Tutorial 2: How to Generate a Histogram. Problem. Using the data in. (A practical guide for those unfortunate enough to have to actually do it.) .. SPSS version 15 but this is now superseded by version 16 and version 17 is on its. SPSS uses several windows to manage data, output, graphs, and advanced .. Guide to SPSS. Barnard College – Biological Sciences. Look at the results in .

Catalina 18 4 4. Firebird 18 1 1. Grand Prix 19 3 2. Le Mans 19 3 3. Phoenix 19 3. Sunbird 24 2 2. The data set has missing values which were left blank, and the long character variable make which contains blanks. Thus fixed field input was used with columns ranges specified. T-tests We can use the t-test command to determine whether the average mpg for domestic cars differ from the mean for foreign cars.

Here is the output produced by the t-test.

The results show that foreign cars have significantly higher gas mileage mpg than domestic cars. Note that the overall N is 71 not This is because mpg was missing for 3 of the observations, so those observations were omitted from the analysis. Note that the output provides two t values, one assuming that the variances are Equal and another assuming that the variances are Unequal.

However, this test is very sensitive to issues other than variances such as homogeneity , so we often ignore it. When deciding between the t-test assuming equal or unequal variances, instead look at the standard deviations in the Group Statistics table. If the standard deviation of one variable is not more than about twice the other variable, then it is probably safe to use the equal variances version of the t-test. If the standard deviation of one variable is much larger than that of the other variable, then you may want to use the t-test with the unequal variances assumed.

Chi-square tests We can use the crosstabs command to examine the repair records of the cars rep78, where 1 is the worst repair record, 5 is the best repair record by foreign foreign coded 1, domestic coded 0. Use the chissq keyword on the statistics subcommand to request a chi-square test.

## An overview of statistical tests in SPSS | SPSS Learning Modules

This test determines if these two variables are independent. The syntax is shown below. The results are shown below, presenting the crosstab first and then following with the chi-square test.

Notice that SPSS tells us that four of 10 cells have an expected value of less than five. The chi-square is not really valid when you have cells with expected values less than five. The results of the correlations command are shown below. The output is a correlation matrix for price, mpg and weight.

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The off-diagonal cells have three entries: correlation coefficient, P value and number of cases N. The p-value is the two-tailed p-value for the hypothesis test that the correlation is 0. By looking at the sample sizes, we can see how the correlations command handles the missing values. Since mpg had three missing values, all of the correlations with mpg have an N of The rest of the correlations were based on an N of This is called pairwise deletion of missing data.

Since SPSS used the maximum number of non-missing values for each pair of variables it uses pairwise deletion. It is possible to ask SPSS for correlations only on the cases having complete data for all of the variables on the variables subcommand.

## SPSS Tutorials: Creating a Codebook

This is called listwise deletion of missing data, when any of the variables are missing for a case, the entire case will be omitted from analysis. This is demonstrated in the syntax below. Notice that the correlations command can be abbreviated as corr. The results of this command are shown below. Regression Regression is a technique used to find the best linear prediction of a criterion variable from a set of predictor variables.

We can use the regression command as in the example below. The method subcommand names the predictor variables mpg and weight, and the enter keyword causes both variables to enter the equation at the same time. You should note the following two points in looking at the output below. The regression command deletes missing cases using listwise deletion. If you have a large amount of missing data you may lose too many cases unless you use some method for estimating missing values.

The predicted regression coefficient B for weight is 1.

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One reason for this may be the high correlation between mpg and weight. The results are shown below. Analysis of variance and analysis of covariance To compare the average prices among the cars in the different repair groups we use Analysis of Variance.

Now the data will appear in SPSS. Even if your workbook only has a single sheet, you must still tell SPSS which sheet you want to read in.

If you want to refer to a sheet by its position instead of its name -- e. It's only possible to import one sheet at a time, even if there are multiple sheets in your workbook. If you want to import more than one sheet, you will need to read in each sheet individually. These types of data files are simple to create and are not tied to a proprietary software, so they are a popular choice for data files.

While many computers will automatically open these file types in a spreadsheet software like Microsoft Excel, they can be opened and edited using any text editor program. There are several different patterns used to delineate the start and end of a particular variable, and SPSS must know what pattern to follow in order to read the data correctly. In general, there are two patterns that SPSS recognizes: Delimited data: Each observation is delimited, or separated, by a particular character.

Common characters used for delimiters include commas, tabs, and whitespace. ID,Age,Gender A,41,F A,36,M C,27,F Fixed-width data: Rather than using delimiters between observations, the values of the variables are aligned vertically, so that a given variable always begins in a certain column position. In the below example, ID always begins in column 1; Age always begins in column 10; and Gender always begins in column This file type can contain fixed-width or delimited data.

Traditionally, the first row of a CSV file contains the variable names separated by a comma , and the first row of data begins on the second line. Missing values are denoted using adjacent delimiters. Locate your file and click on it to select it, then click OK.

## 3. Basic Components of SPSS Statistics

This will start the Text Import Wizard process, which will walk you through the process of specifying how SPSS should read and interpret the data file.

Step 1 of 6 This window provides a preview of the data in your text file. The first step is to indicate whether the data matches a predefined format, which would be a format saved from a previous text file imported with the Text Import Wizard.

In most cases there will not be a predefined format. Step 2 of 6 If your data did not match a predefined format you will need to tell SPSS how your data is arranged, so that it understands where one column ends and the next begins. For text files, there are two types of "arrangements": delimited and fixed width. If you are importing a CSV file, you have delimited data. You will also need to tell SPSS if the datafile contains variable names. For CSV files, variable names are typically included on the first line of the data file, before the data begins; however, some datafiles do not include variable names.

If necessary, choose the symbol used to denote decimals. For CSV files, the first row typically contains the variable names, and the data values begin on line 2. However, you can choose to skip over certain lines if necessary. One example where this occurs is in Qualtrics survey data output to CSV: The second row frequently contains variable labels, and oftentimes there may be a third row containing import IDs, and the data actually begins on line 4.

Step 4 of 6 In the "Which delimiters appear between variables" area, select the check box that reflects the delimiter used in your data. The delimiter is what is used to separate values from each other within the data. If the text file is a. If you do not know which delimiter is used in the text file, refer to documentation that is associated with your data or ask someone who knows how the data file was created.

The options Remove leading spaces from string values and Removing trailing spaces from string values were added in SPSS version If you are using SPSS version 24 or earlier, you will not see these options on this window. SPSS attempts to guess what delimiters your file is using. Notice how that affects the parsing of variable Major: Because SPSS thinks that both spaces and commas were used as delimiters, it thinks that the spaces occurring in the names of the majors delimit observations for subsequent variables, and hence, SPSS interprets individual words as readings for the adjacent variable s here, variables Height, Weight, and Smoking.

Notice, however, that there was still at least one case where the observation for Major was incorrectly split across two columns.

Notice how the value has double quotes " before the first word and after the last word.

These quotes are being used as the text qualifiers; that is, they indicate where the observation starts and ends.Analysis of variance and analysis of covariance To compare the average prices among the cars in the different repair groups we use Analysis of Variance.

AMC Concord 3 2. From SPSS Viewer, outputs can be selected, copied and pasted into any spreadsheet software, word processors or graphical presentation software. Monza 24 2 2. Malibu 22 3 3. The results are shown below, presenting the crosstab first and then following with the chi-square test. If the canvas already displays a chart, the new chart from the gallery will replace the axis set and graphic elements on the existing chart. When deciding between the t-test assuming equal or unequal variances, instead look at the standard deviations in the Group Statistics table.

In order to demonstrate how these commands handle missing values, some of the values of mpg have been set to be missing for the AMC cars. Cougar 14 4 3.

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