how spss is used in data analysis?
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SPSS is short for Statistical Package for the Social Sciences, and it's used by various kinds of researchers for complex statistical data analysis. ... Most top research agencies use SPSS to analyze survey data and mine text data so that they can get the most out of their research projects.
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Social scientists use social statistics for many purposes, including: the evaluation of the quality of services available to a group or organization, analyzing behaviors of groups of people in their environment and special situations, determining the wants of people through statistical sampling.
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X-bar and s charts are used to monitor the mean and variation of a process based on samples taken from the process at given times (hours, shifts, days, weeks, months, etc.). The measurements of the samples at a given time constitute a subgroup.
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['In the SPSS Data Editor menu, go to Transform>Compute..', 'In the Compute Variable dialog box, type in any name that helps you remember that the new column will simply hold a constant value of one. ... ', 'In the box labeled Numeric Expression, simply type the number 1 and then click OK.']
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['Click Analyze -> Descriptive Statistics -> Descriptives.', 'Drag the variable of interest from the left into the Variables box on the right.', 'Click Options, and select Mean and Standard Deviation.', 'Press Continue, and then press OK.', 'Result will appear in the SPSS output viewer.']
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SPSS measurement levels are limited to nominal (i.e. categorical), ordinal (i.e. ordered like 1st, 2nd, 3rd…), or scale. Essentially, a scale variable is a measurement variable — a variable that has a numeric value. Variables with numeric responses are assigned the scale variable label by default.
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Preparing Analysis Data PCA should be used mainly for variables which are strongly correlated. If the relationship is weak between variables, PCA does not work well to reduce data. Refer to the correlation matrix to determine. In general, if most of the correlation coefficients are smaller than 0.3, PCA will not help.
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R has stronger object-oriented programming facilities than SPSS whereas SPSS graphical user interface is written using Java language. It is mainly used for interactively and statistical analysis. ... On the other hand, Decision trees in IBM SPSS are better than R because R does not offer many tree algorithms.
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['Analysis of variance (ANOVA)', 'Chi-squared test.', 'Correlation.', 'Factor analysis.', 'Mann–Whitney U.', 'Mean square weighted deviation (MSWD)', 'Pearson product-moment correlation coefficient.', 'Regression analysis.']
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['Identify the Job(s) to be analyzed.', 'Determine the procedures to be used (methods) in collecting job data.', 'Implement the job analysis methods.', 'Review the data collected through Job Analysis.', 'Summarize and document the data collected.']
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Statistical analysis software, such as SPSS, is often used to analyze quantitative data. Qualitative data describes qualities or characteristics. It is collected using questionnaires, interviews, or observation, and frequently appears in narrative form.
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Hypothesis testing is used to assess the plausibility of a hypothesis by using sample data. The test provides evidence concerning the plausibility of the hypothesis, given the data. Statistical analysts test a hypothesis by measuring and examining a random sample of the population being analyzed.
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Data analysis is the process of working on data with the purpose of arranging it correctly, explaining it, making it presentable, and finding a conclusion from that data. It is done for finding useful information from data to make rational decisions.
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['Descriptive Analysis. Descriptive analysis provides information on the basic qualities of data and includes descriptive statistics such as range, minimum, maximum, and frequency. ... ', 'Measures of Central Tendency. ... ', 'Standard Deviation. ... ', 'Inferential Analysis. ... ', 'Normal Distribution. ... ', 'Non-Normal Distribution.']
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Statistical methods involved in carrying out a study include planning, designing, collecting data, analysing, drawing meaningful interpretation and reporting of the research findings. The statistical analysis gives meaning to the meaningless numbers, thereby breathing life into a lifeless data.
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The data used in cluster analysis can be interval, ordinal or categorical. However, having a mixture of different types of variable will make the analysis more complicated.
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Two types of statistical methods are used in analyzing data: descriptive statistics and inferential statistics. Descriptive statistics are used to synopsize data from a sample exercising the mean or standard deviation. Inferential statistics are used when data is viewed as a subclass of a specific population.