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This course takes the viewer through the key steps of entering and processing questionnaire/survey data and Likert scales in SPSS, including creating variables in SPSS, entering value labels, using statistical analyses to identify data entry errors, recoding Likert items, computing total (composite) scores, conducting reliability analyses of Likert scales, and computing other statistics, including frequencies, descriptive statistics (mean and standard deviation), and correlations. In addition to this, a number of additional database management skills in SPSS are also covered. Created by an award-winning university instructor with a focus on simple and accurate (step by step) explanations of the material.
Specifically, in this course you will learn the following:
This course is perfect for professionals looking to increase the data processing skills in SPSS, for those working on survey research, and for students working on theses or dissertations (or other research projects).
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Section 1: Introduction to the Course | |||
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Lecture 1 | 03:03 | ||
In this video, an overview of the topics we'll be covering in the course is provided along with an introduction of the instructor. |
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Section 2: Entering Questionnaire/Survey Data into SPSS | |||
Lecture 2 | 09:15 | ||
In this video, we'll take a look at how to set up a data file in SPSS based on a sample questionnaire/survey. Moving step by step through the survey, we'll create the variables, enter value labels, and talk about how to enter both numeric and text values into SPSS. Note: The SPSS files for the course are located in this folder (named SPSS Files Survey and Likert Scales). There are SPSS data files (extension: .sav), as well as output files (.spv) and syntax files (.sps) where relevant. Also, all Word and PDF files are located within each folder of interest for a given lecture. For example, there are 3 files in this folder: a copy of the questionnaire form used in the lecture (both in Word and PDF formats) and the SPSS output from this lecture (in PDF format). |
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Lecture 3 | 08:50 | ||
In this video, we'll enter values from the survey (created in the previous video) for practice. After watching this video, you should have a good understanding of how to enter survey data into SPSS. |
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Section 3: Processing Survey Data - Recoding, Total Scores, and Syntax | |||
Lecture 4 | 04:14 | ||
In this video, we'll see how to use the Compute procedure in SPSS to create a new variable that is equal to the sum of two or more other variables. This procedure is used very often in survey/questionnaire data, particularly when creating composite scores (scores that are the sum of a number of Likert-type survey questions). |
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Lecture 5 | 06:27 | ||
In this video, we'll see how to use the Compute procedure in SPSS to create a new variable that is equal to the sum of two or more other variables. This video focuses on the sum function, which is most useful to use when missing values are treated as zeros. |
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Lecture 6 | 12:37 | ||
In this video, we'll take our first look at the power of using syntax when processing survey data and for data file management in general. We will also look at how to recode responses into a dichotomous outcome (correct/incorrect in this example) using multiple choice test items. This approach is useful for processing a variety of different kinds of variables in SPSS, including multiple choice test items (Part 1 of 2). |
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Lecture 7 | 13:15 | ||
In this video, we'll continue our look at the power of using syntax when processing survey data and for data file management in general. We will also look at how to recode responses into a dichotomous outcome (correct/incorrect in this example) using multiple choice test items. This approach is useful for processing a variety of different kinds of variables in SPSS, including multiple choice test items (Part 2 of 2). |
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Section 4: Creating and Analyzing Likert Scales | |||
Lecture 8 | 08:40 | ||
In this video we do two things: (1) we take a look at the value labels command in SPSS, including the very useful feature of copying value labels across several variables at once, and (2) we provide an introduction to Likert scales. |
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Lecture 9 | 03:54 | ||
In this video, we take a look at how to create a professional looking Likert scale in Word. This video should be helpful for those who are looking to create their own surveys in Word and for those who are interested in learning more about the very useful insert table command in Word. |
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Lecture 10 | 09:35 | ||
In this video we take a look at Coefficient alpha, which is a measure of internal consistency reliability (Coefficient alpha is also known as Cronbach's alpha, as it was proposed by Lee Cronbach). Coefficient alpha is one of the most common methods of establishing the reliability of a Likert scale. |
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Lecture 11 | 14:15 | ||
In this video, we take our first look at how to reverse code Likert items (variables) in SPSS using the Compute > Recode into Different Variables procedure. (Recoding variables is a very important topic that is often confused and/or applied incorrectly.) In SPSS, we'll recode items on a Likert scale that are known as negative items, which are statements where people who are high on a trait (or construct) answer with a low value on the item (such as a "1" or "2"). These types of items need to be reverse coded prior to being added to create a total (composite) score. |
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Section 5: Survey Data and Likert Scales in SPSS - Data Set Example with Syntax | |||
Lecture 12 | 11:24 | ||
In this video, we take a look at a second example of questionnaire/survey data in SPSS. In this data file, we look at the responses of N=125 observations on 44 different variables. This video specifically covers value labels, missing values, and how to use statistical analyses to scan for and identify potential data entry errors. |
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Lecture 13 | 08:23 | ||
In this video, we take a look at our first Likert scale in the data file, the Satisfaction with Life Scale (Diener et al.). We look at each of the items on the scale (the scale is attached) and then create a total score using the compute procedure in SPSS. We then calculate the reliability of the scale for the N = 125 participants using coefficient alpha. |
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Lecture 14 | 08:09 | ||
In this video, we take a look at our second Likert scale in the data file, the Rosenberg Self-Esteem Scale. This scale consists of 10 items ona 4-point Likert response format (with negative items). In this video we identify and then reverse code the negative items on the scale in SPSS. |
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Lecture 15 | 07:01 | ||
In this video, we use the compute procedure in SPSS to create a total score for the Rosenberg Self-Esteem Scale (with negative items included where appropriate). We then calculate the reliability of the scale using coefficient alpha. |
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Lecture 16 | 10:43 | ||
In this video, we take a look at our last Likert scale in the data file, the Interpersonal Reactivity Index (a measure of empathy). This scale consists of 28 items on a 5-point Likert response format (with negative items). In this video we identify and then reverse code the negative items on the scale in SPSS. |
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Lecture 17 | 13:11 | ||
In this video, we use the compute procedure in SPSS to create the total score for each of the four subscales of the Interpersonal Reactivity Index. We then calculate the reliability of each of the four subscales using coefficient alpha. |
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Section 6: Bonus Features: Data File Management and Descriptive Statistics in SPSS | |||
Lecture 18 | 02:41 | ||
In this video, how to calculate the mean, median, and mode is illustrated using the frequencies procedure in SPSS. |
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Lecture 19 | 02:50 | ||
In this video, how to obtain the mean and standard deviation is illustrated using the frequencies procedure in SPSS. |
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Lecture 20 | 07:41 | ||
In this video, the mean and standard deviation is obtained for separate groups of a categorical variable using the compare means procedure in SPSS. In this example, instead of obtaining an overall mean on the variable satisfaction, a separate mean satisfaction score is obtained for two groups. |
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Lecture 21 | 07:20 | ||
In this video, we take a look at how to insert one or more variables (columns) in SPSS, which is often a very useful procedure in managing a data file. |
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Lecture 22 | 02:51 | ||
In this video, we take a look at how to insert one or more cases (rows) in SPSS. As with inserting variables, this can be very useful when working with survey/questionnaire data. |
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Lecture 23 | 05:38 | ||
In this video, we take a look at how to edit a number of default options in SPSS, which allows for greater control and can also save time when working in SPSS. |
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Section 7: Conclusion | |||
Lecture 24 | 00:55 | ||
In this video, we wrap things up with some final thoughts and briefly cover some additional statistics resources available by Quantitative Specialists. |
Quantitative Specialists (QS) was founded by an award-winning university instructor who has taught statistics courses for over 15 years. At QS, we are passionate about all things statistical, especially in helping others understand this often-feared subject matter. Our focus is in helping you to succeed in all your statistics work!