Spss survival manual 6th edition pdf free download

Spss survival manual 6th edition pdf free download

SPSS Survival Manual PDF – Free Download,Document details

SPSS Survival Manual [6 ed.] X, The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis softwa. 1, 86 2MB. English Pages [] Year Report DMCA / Copyright. DOWNLOAD FILE 20/06/ · HomeExploreSPSS Survival Manual (6th Edition) View in Fullscreen SPSS Survival Manual (6th Edition) Like this book? You can publish your book online for free in a Download Download Spss Survival Manual [PDF] Type: PDF Size: MB Download as PDF Download as DOCX Download as PPTX Download Original PDF This document was Get SPSS Survival Manual: A step by step guide to data analysis using SPSS, 4th Edition pdf free download and get a clearer picture of all that has to do with this very issue. SPSS Survival 16/07/ · The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software. In her bestselling guide, Julie Pallant takes you ... read more

In this book I try to translate statistics into a language that can be more easily understood and digested. The SPSS Survival Manual is presented in a structured format, setting out step by step what you need to do to prepare and analyse your data. Think of your data as the raw ingredients in a recipe. Depending on what ingredients you have available, different options may, or may not, be suitable. There is no point planning to make beef stroganoff if all you have available is chicken. Planning and preparation are an important part of the process both in cooking and in data analysis. chocolate cake is supposed to look?

The same questions apply equally well to the process of analysing your data. You must plan your experiment or survey so that it provides the information you need, in the correct format. You must prepare your data file properly and enter your data carefully. You should have a clear idea of your research questions and how you might go about addressing them. You need to know what statistical techniques are available, what sort of variables are suitable and what are not. You must be able to perform your chosen statistical technique e. t-test correctly and interpret the output. STRUCTURE OF THIS BOOK This SPSS Survival Manual consists of 22 chapters, covering the research process from designing a study through to the analysis of the data and presentation of the results. It is broken into five main parts. Part One Getting started covers the preliminaries: designing a study, preparing a codebook and becoming familiar with IBM SPSS.

In Part Two Preparing the data file you will be shown how to prepare a data file, enter your data and check for errors. Preliminary analyses are covered in Part Three, which includes chapters on the use of descriptive statistics and graphs; the manipulation of data; and the procedures for checking the reliability of scales. You will also be guided, step by step, through the sometimes difficult task of choosing which statistical technique is suitable for your data. In Part Four the major statistical techniques that can be used to explore relationships are presented e. correlation, partial correlation, multiple regression, logistic regression and factor analysis. These chapters summarise the purpose of each technique, the underlying assumptions, how to obtain results, how to interpret the output, and how to present these results in your thesis or report.

Part Five discusses the statistical techniques that can be used to compare groups. These include non-parametric techniques, t-tests, analysis of variance, multivariate analysis of variance and analysis of covariance. USING THIS BOOK To use this book effectively as a guide to IBM SPSS, you need some basic computer skills. In the instructions and examples provided throughout the text I assume that you are already familiar with using a personal computer, particularly the Windows functions. I have listed below some of the skills you will need. Seek help if you have difficulty with any of these operations. It is assumed that you have been exposed to the fundamentals of statistics and have access to a statistics text. It is an enormously powerful data analysis package that can handle very complex statistical procedures. This manual does not attempt to cover all the different statistical techniques available in the program.

Only the most commonly used statistics are covered. It is designed to get you started and to develop your confidence in using the program. Depending on your research questions and your data, it may be necessary to tackle some of the more complex analyses available in IBM SPSS. There are many good books available covering the various statistical techniques in more detail. Read as widely as you can. Browse the shelves in your library, look for books that explain statistics in a language that you understand well, at least some of it anyway! Collect this material together to form a resource to be used throughout your statistics classes and your research project.

It is also useful to collect examples of journal articles where statistical analyses are explained and results are presented. You can use these as models for your final writeup. The SPSS Survival Manual is suitable for use as both an in-class text, where you have an instructor taking you through the various aspects of the research process, and as a self-instruction book for those conducting an individual research project. If you are teaching yourself, be sure to actually practise using IBM SPSS by analysing the data that is included on the website accompanying this book see p. ix for details. The best way to learn is by actually doing, rather than just reading. This will improve your confidence and also allow you to check that you are performing the analyses correctly. Sometimes you may find that the output you obtain is different from that presented in the book. This is likely to occur if you are using a different version of IBM SPSS from that used throughout this book IBM SPSS Statistics v IBM SPSS regularly updates its products, which is great in terms of improving the program, but it can lead to confusion for students who find that what is on the screen differs from what is in the book.

Usually the difference is not too dramatic, so stay calm and play detective. The information may be there, but just in a different form. For information on changes to the IBM SPSS products you may like to go to the IBM SPSS website www. RESEARCH TIPS If you are using this book to guide you through your own research project, there are a few additional tips I would like to recommend. Draw on existing theories and research to guide the design of your project. Know what you are trying to achieve and why. Anticipate potential problems and hiccups—every project has them! Know what statistics you intend to employ and use this information to guide the formulation of data collection materials.

Make sure that you will have the right sort of data to use when you are ready to do your statistical analyses. Keep careful notes of all relevant research, references etc. Work out an effective filing system for the mountain of journal articles you will acquire and, later on, the output from IBM SPSS. It is easy to become disorganised, overwhelmed and confused. When using IBM SPSS to conduct your analyses, keep careful records of what you do. I recommend to all my students that they buy a spiralbound exercise book to record every session they spend on IBM SPSS. You should record the date, new variables you create, all analyses you perform and the names of the files where you have saved the output.

If you have a problem or something goes horribly wrong with your data file, this information can be used by your supervisor to help rescue you! If this is your first exposure to IBM SPSS and data analysis, there may be times when you feel yourself becoming overwhelmed. Take some deep breaths and use some positive self-talk. Just take things step by step—give yourself permission to make mistakes and become confused sometimes. If it all gets too much then stop, take a walk and clear your head before you tackle it again. Most students find IBM SPSS quite easy to use, once they get the hang of it. Like learning any new skill, you just need to get past that first feeling of confusion and lack of confidence.

The research process, particularly the data entry and data analysis stages, always takes longer than expected, so allow plenty of time for this. Make use of other students for emotional and practical support during the data analysis process. Social support is a great buffer against stress! Further reading and resource material is recommended throughout the different chapters in the book. You should try to read as broadly as you can, particularly if tackling some of the more complex statistical procedures. The data you enter must come from somewhere—responses to a questionnaire, information collected from interviews, coded observations of actual behaviour, or objective measurements of output or performance. The data are only as good as the instrument that you used to collect them and the research framework that guided their collection. In this chapter a number of aspects of the research process are discussed that have an impact on the potential quality of the data.

First, the overall design of the study is considered; this is followed by a discussion of some of the issues to consider when choosing scales and measures; and finally, some guidelines for preparing a questionnaire are presented. PLANNING THE STUDY Good research depends on the careful planning and execution of the study. There are many excellent books written on the topic of research design to help you with this process—from a review of the literature, formulation of hypotheses, choice of study design, selection and allocation of participants, recording of observations and collection of data. Decisions made at each of these stages can affect the quality of the data you have to analyse and the way you address your research questions. In designing your own study I would recommend that you take your time working through the design process to make it the best study that you can produce.

Reading a variety of texts on the topic will help. A few good, easy-to-follow titles are listed in the Recommended reading section at the back of the book. experiment, survey, observation is the best way to address your research question. There are advantages and disadvantages to all types of research approaches; choose the most appropriate approach for your particular research question. Have a good understanding of the research that has already been conducted in your topic area. There are advantages and disadvantages to each approach, so weigh up each approach carefully.

Using only two levels or groups means fewer participants are required, but it limits the conclusions that you can draw. Is a control group necessary or desirable? Will the lack of control group limit the conclusions that you can draw? So plan accordingly. Err on the side of pessimism rather than optimism. With small groups, it is difficult to detect statistically significant differences between groups an issue of power, discussed in the introduction to Part Five. There are calculations you can perform to determine the sample size that you will need. See, for example, Stangor This reduces the problem associated with non-equivalent groups in betweengroups designs. You may be able to statistically control for differences that you identify e. using analysis of covariance.

It is a good idea to include a number of different measures—some measures are more sensitive than others. than others. These are variables that could provide an alternative explanation for your results. Sometimes they are hard to spot when you are immersed in designing the study yourself. Always have someone else supervisor, fellow researcher check over your design before conducting the study. Do whatever you can to control for these potential confounding variables. Knowing your topic area well can also help you identify possible confounding variables. If there are additional variables that you cannot control, can you measure them? By measuring them, you may be able to control for them statistically e. Wherever possible, pilot-test on the same type of people who will be used in the main study e. adolescents, unemployed youth, prison inmates.

You need to ensure that your respondents can understand the survey or questionnaire items and respond appropriately. Pilot-testing should also pick up any questions or items that may offend potential respondents. If you are using equipment, make sure it works properly. If you are using different experimenters or interviewers, make sure they are properly trained and know what to do. If different observers are required to rate behaviours, make sure they know how to appropriately code what they see. Have a practice run and check for inter-rater reliability i. how consistent scores are from different raters. Pilot-testing of the procedures and measures helps you identify anything that might go wrong on the day and any additional contaminating factors that might influence the results.

Some of these you may not be able to predict e. This might involve measuring output or performance on some objective criteria, or rating behaviour according to a set of specified criteria. There are many thousands of validated scales that can be used in research. Finding the right one for your purpose is sometimes difficult. A thorough review of the literature in your topic area is the first place to start. What measures have been used by other researchers in the area? Sometimes the actual items that make up the scales are included in the appendix to a journal article; otherwise you may need to trace back to the original article describing the design and validation of the scale you are interested in.

It is very important, however, to properly acknowledge each of the scales you use, giving full reference details. In choosing appropriate scales there are two characteristics that you need to be aware of: reliability and validity. Both of these factors can influence the quality of the data you obtain. When reviewing possible scales to use, you should collect information on the reliability and validity of each of the scales. No matter how good the reports are concerning the reliability and validity of your scales, it is important to pilot-test them with your intended sample. Sometimes scales are reliable with some groups e. adults with an English-speaking background , but are totally unreliable when used with other groups e. children from non-English-speaking backgrounds.

Reliability The reliability of a scale indicates how free it is from random error. The test-retest reliability of a scale is assessed by administering it to the same people on two different occasions, and calculating the correlation between the two scores obtained. High test-retest correlations indicate a more reliable scale. You need to take into account the nature of the construct that the scale is measuring when considering this type of reliability. A scale designed to measure current mood states is not likely to remain stable over a period of a few weeks. The test-retest reliability of a mood scale, therefore, is likely to be low. You would, however, hope that measures of stable personality characteristics would stay much the same, showing quite high test-retest correlations. The second aspect of reliability that can be assessed is internal consistency. This is the degree to which the items that make up the scale are all measuring the same underlying attribute i.

Internal consistency can be measured in a number of ways. This statistic provides an indication of the average correlation among all of the items that make up the scale. Values range from 0 to 1, with higher values indicating greater reliability. While different levels of reliability are required, depending on the nature and purpose of the scale, Nunnally recommends a minimum level of. Cronbach alpha values are dependent on the number of items in the scale. When there are a small number of items in the scale fewer than 10 , Cronbach alpha values can be quite small. In this situation it may be better to calculate and report the mean inter-item correlation for the items. Optimal mean inter-item correlation values range from. Validity The validity of a scale refers to the degree to which it measures what it is supposed to measure.

The validation of a scale involves the collection of empirical evidence concerning its use. The main types of validity you will see discussed are content validity, criterion validity and construct validity. Content validity refers to the adequacy with which a measure or scale has sampled from the intended universe or domain of content. Criterion validity concerns the relationship between scale scores and some specified, measurable criterion. Construct validity involves testing a scale not against a single criterion but in terms of theoretically derived hypotheses concerning the nature of the underlying variable or construct. The construct validity is explored by investigating its relationship with other constructs, both related convergent validity and unrelated discriminant validity. An easy-to-follow summary of the various types of validity is provided in Streiner and Norman If you intend to use scales in your research, it would be a good idea to read further on this topic: see Kline for information on psychological tests, and Streiner and Norman for health measurement scales.

Bowling also has some great books on health and medical scales. This may involve obtaining demographic information from participants prior to exposing them to some experimental manipulation. Alternatively, it may involve the design of an extensive survey to be distributed to a selected sample of the population. A poorly planned and designed questionnaire will not give good data with which to address your research questions. In preparing a questionnaire, you must consider how you intend to use the information; you must know what statistics you intend to use. Depending on the statistical technique you have in mind, you may need to ask the question in a particular way, or provide different response formats. Some of the factors you need to consider in the design and construction of a questionnaire are outlined in the sections that follow. This section only briefly skims the surface of questionnaire design, so I would suggest that you read further on the topic if you are designing your own study.

A really great book for this purpose is De Vaus Question types Most questions can be classified into two groups: closed or open-ended. A closed question involves offering respondents a number of defined response choices. They are asked to mark their response using a tick, cross, circle, etc. For example: What is the highest level of education you have completed? please tick 1. Primary school 2. Some secondary school 3. Completed secondary school 4. Trade training 5. Undergraduate university 6. Postgraduate university Closed questions are usually quite easy to convert to the numerical format required for IBM SPSS. For example, Yes can be coded as a 1, No can be coded as a 2; Males as 1, Females as 2.

In the education question shown above, the number corresponding to the response ticked by the respondent would be entered. For example, if the respondent ticked Undergraduate university, this would be coded as a 5. Numbering each of the possible responses helps with the coding process. For data entry purposes, decide on a convention for the numbering e. in order across the page, and then down , and stick with it throughout the questionnaire. Sometimes you cannot guess all the possible responses that respondents might make—it is therefore necessary to use open-ended questions. The advantage here is that respondents have the freedom to respond in their own way, not restricted to the choices provided by the researcher.

For example: What is the major source of stress in your life at the moment? These categories are usually identified after looking through the range of responses actually received from the respondents. Some possibilities could also be raised from an understanding of previous research in the area. Each of these response categories is assigned a number e. More details on this are provided in the section on preparing a codebook in Chapter 2. Sometimes a combination of both closed and open-ended questions works best. This involves providing respondents with a number of defined responses, and also an additional category other that they can tick if the response they wish to give is not listed. A line or two is provided so that they can write the response they wish to give. This combination of closed and open-ended questions is particularly useful in the early stages of research in an area, as it gives an indication of whether the defined response categories adequately cover all the responses that respondents wish to give.

Response format In asking respondents a question, you also need to decide on a response format. The type of response format you choose can have implications when you come to do your statistical analysis. Some analyses e. correlation require scores that are continuous, from low through to high, with a wide range of scores. If you had asked respondents to indicate their age by giving them a category to tick e. less than 30, between 31 and 50, and over 50 , these data would not be suitable to use in a correlational analysis. So, if you intend to explore the correlation between age and, say, self-esteem, you will need to ensure that you ask respondents for their actual age in years.

women over 30! Try to provide as wide a choice of responses to your questions as possible. You can always condense things later if you need to see Chapter 8. You will need to make a decision concerning the number of response steps e. DeVellis has a good discussion concerning the advantages and disadvantages of different response scales. Whatever type of response format you choose, you must provide clear instructions. Do you want your respondents to tick a box, circle a number, make a mark on a line? For some respondents, this may be the first questionnaire that they have completed. Give clear instructions, provide an example if appropriate, and always pilot-test on the type of people that will make up your sample. Iron out any sources of confusion before distributing hundreds of your questionnaires.

In designing your questions, always consider how a respondent might interpret the question and all the possible responses a person might want to make. For example, you may want to know whether people smoke or not. You might ask the question: Do you smoke? please tick Yes No In trialling this questionnaire, your respondent might ask whether you mean cigarettes, cigars or marijuana. Is knowing whether they smoke enough? The message here is to consider each of your questions, what information they will give you and what information might be missing. Wording the questions There is a real art to designing clear, well-written questionnaire items. Although there are no clear-cut rules that can guide this process, there are some things you can do to improve the quality of your questions, and therefore your data.

For further suggestions on writing questions, see De Vaus and Kline The flow chart shown on the next page outlines the main steps that are needed. In this chapter I will lead you through the process of creating a data file and entering the data. The first step is to check and modify, where necessary, the options that IBM SPSS uses to display the data and the output that is produced. The final step is to enter the data—that is, the values obtained from each participant or respondent for each variable. To illustrate these procedures I have used the data file survey.

sav, which is described in the Appendix. The codebook used to generate these data is also provided in the Appendix. You can set up a basic data file on Excel and enter the data at home. When complete, you can then import the file into IBM SPSS and proceed with the data manipulation and data analysis stages. The instructions for using Excel to enter the data are provided later in this chapter. The options allow you to define how your variables will be displayed, the type of tables that will be displayed in the output and many other aspects of the program. Some of this will seem confusing at first, but once you have used the program to enter data and run some analyses you may want to refer back to this section.

If you are sharing a computer with other people e. in a computer lab , it is worth being aware of these options. Sometimes other students will change these options, which can dramatically influence how the program appears. It is useful to know how to change things back to the way you want them. To open the Options screen, click on Edit from the menu at the top of the screen and then choose Options. The screen shown in Figure 4. I have described the key ones below, organised by the tab they appear under. To move between the various tabs, just click on the one you want. General tab When you come to do your analyses, you can ask for your variables to be listed in alphabetical order or by the order in which they appear in the file. I always use the file order, because this is consistent with the order of the questionnaire items and the codebook. To keep the variables in file order, just make sure the option File in the Variable Lists section is selected. Figure 4. This will stop you getting some very strange numbers in your output for the statistical analyses.

Data tab Click on the Data tab to make changes to the way that your data file is displayed. If your variables do not involve values with decimal places, you may like to change the display format for all your variables. In the section labelled Display Format for New Numeric Variables, change the Decimal Places value to 0. This means that all new variables will not display any decimal places. This reduces the size of your data file and simplifies its appearance. Output tab The options in this section allow you to customise how you want the variable names and value labels displayed in your output. In the very bottom section under Variable values in labels are shown as: choose Values and Labels from the dropdown options. This will allow you to see both the numerical values and the explanatory labels in the tables that are generated in the Viewer window.

In the section labelled Output Display choose Pivot tables and charts. This is particularly important if you are intending to use the Nonparametric Tests procedures in SPSS. Pivot Tables tab IBM SPSS presents most of the results of the statistical analyses in tables called pivot tables. Under the Pivot Tables tab you can choose the format of these tables from an extensive list. It is a matter of experimenting to find a style that best suits your needs. I use a style called CompactBoxed as this saves space and paper when printing. One other option you might find useful is at the bottom of the Pivot Tables tab—labelled Copying wide tables to the clipboard in rich text form.

Click on the drop-down box and select Shrink width to fit. This is useful when you are pasting output from IBM SPSS to Microsoft Word and the results are too wide for the page a common problem in some of the statistical procedures presented later in the book. You can change the table styles as often as you like—just remember that you have to change the style before you run the analysis. You cannot change the style of the tables after they appear in your output, but you can modify many aspects e. font sizes, column width by using the Pivot Table Editor. This can be activated by double-clicking on the table that you wish to modify. Once you have made all the changes you wish to make on the various Options tabs, click on OK. You can then proceed to define your variables and enter your data. DEFINING THE VARIABLES Before you can enter your data, you need to tell IBM SPSS about your variable names and coding instructions.

You will do this in the Data Editor window see Figure 4. The Data Editor window consists of two different views: Data View and Variable View. You can move between these two views using the little tabs at the bottom left-hand side of the screen. You will notice that in the Data View window each of the columns is labelled var see Figure 4. These will be replaced with the variable names that you listed in your codebook. Down the side you will see the numbers 1, 2, 3 and so on. These are the case numbers that IBM SPSS assigns to each of your lines of data. These are not the same as your ID numbers, and these case numbers change if you sort your file or split your file to analyse subsets of your data.

Procedure for defining your variables To define each of the variables that make up your data file, you first need to click on the Variable View tab at the bottom left of your screen. In this view see Figure 4. Your job now is to define each of your variables by specifying the required information for each variable listed in your codebook. Some of the information you will need to provide yourself e. name ; other bits are provided automatically using default values. These default values can be changed if necessary. The key pieces of information that are needed are described below. The headings I have used correspond to the column headings displayed in the Variable View.

I have provided the simple step-by-step procedures below; however, there are a number of shortcuts that you can use once you are comfortable with the process. You should become familiar with the basic techniques first. Keep these variable names as short as possible, not exceeding 64 characters. They must follow the naming conventions specified by IBM SPSS listed in Chapter 2. Each variable name must be unique, must start with a letter, and cannot contain spaces or symbols. For ideas on how to label your variables, have a look at the codebooks provided in the Appendix. These list the variable names used in data files that accompany this book see p. ix for details of these files. Type The default value for Type that will appear automatically as you enter your first variable name is Numeric. For most purposes, this is all you will need to use. There are some circumstances where other options may be appropriate. For example, if you need to enter text information e. A Date option is also available if your data includes dates.

To change the variable type, click in the cell and a box with three dots should appear giving you the options available. You can also use this window to adjust the width of the variable and the number of decimal places. Width The default value for Width is 8 unless this has been changed using the Options instructions presented earlier in this section. This is usually sufficient for most data. If your variable has very large values or you have requested a string variable , you may need to change this default value; otherwise, leave it as is. Decimals The default value for Decimals is usually 2 however, this can be changed using the Options facility described earlier in this chapter.

If your variable has decimal places, adjust this to suit your needs. Label The Label column allows you to provide a longer description for your variable than used in the Name column. This will be used in the output generated from the analyses conducted by IBM SPSS. For example, you may wish to give the label Total Optimism to your variable TOPTIM. Values In the Values column you can define the meaning of the values you have used to code your variables. I will demonstrate this process for the variable Sex. Click in the cell under the heading Values for the variable you wish to specify. A box with three dots should appear on the right-hand side of the cell. This opens the Value Labels dialogue box.

Click in the box marked Value. Type in 1. Click in the box marked Label. Type in Male. Click on Add. Repeat for females: Value: enter 2, Label: enter Female. When you have finished defining all the possible values as listed in your codebook , click on OK. Missing Sometimes researchers assign specific values to indicate missing values for their data. This is not essential—IBM SPSS will recognise any blank cell as missing data. So if you intend to leave a blank when a piece of information is not available, it is not necessary to do anything with this Variable View column.

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SPSS Survival Manual 7 th edition text book by Julie Pallant. Click here for information on the support website for the 6 th edition. The internationally successful, user-friendly guide that Download Download Spss Survival Manual [PDF] Type: PDF Size: MB Download as PDF Download as DOCX Download as PPTX Download Original PDF This document was SPSS Survival Manual [6 ed.] X, The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis softwa. 1, 86 2MB. English Pages [] Year Report DMCA / Copyright. DOWNLOAD FILE 16/07/ · The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software. In her bestselling guide, Julie Pallant takes you 6/01/ · SPSS SURVIVAL MANUAL 5TH EDITION PDF DOWNLOAD This SPSS SURVIVAL MANUAL 5TH EDITION PDF DOWNLOAD PDF start with Intro, Brief Session up Get SPSS Survival Manual: A step by step guide to data analysis using SPSS, 4th Edition pdf free download and get a clearer picture of all that has to do with this very issue. SPSS Survival ... read more

Click on Utilities from the menu and choose Define Variable Sets. At the end of this chapter, instructions are also given on how to edit a graph to better suit your needs. In designing your own study I would recommend that you take your time working through the design process to make it the best study that you can produce. In the education question shown above, the number corresponding to the response ticked by the respondent would be entered. Start from college textbook, journal, etc plus an extensive directory of product owners manual which is includes many different types of product from different respected brand name. Click on the row number of the next empty row. If you are involved in studying extreme groups e.

With both programs open you can just jump backwards and forwards between the two programs, copying graphs, tables etc. Measure The column heading Measure refers to the level of measurement of each of spss survival manual 6th edition pdf free download variables. SPSS Survival Manual: A step by step guide to data analysis using SPSS, 4th Edition pdf book download. Procedure to generate a matrix of scatterplots 1. Click on all of the individual items that make up the scale e. Get SPSS Survival Manual: A step by step guide to data analysis using SPSS, 4th Edition pdf free download and get a clearer picture of all that has to do with this very issue.