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SPSS is known as the 'Statistical Package for Social Sciences'. This tool was developed by IBM in 1968. This is widely used for doing statistical analysis of the information/ dataset. SPSS is the preferred platform by researchers for performing an extensive analysis of the data. SPSS is also widely used by market researchers, survey companies, government organizations, education researchers, data miners, and marketing companies to process and thoroughly analyze survey data.
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SPSS finds applications in a range of statistical concepts. Listed below are some of the popular statistical concepts that will be used in solving the assignments using the SPSS tool
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Four key programs that you find in SPSS for doing complicated data analysis include:
These are four programs used in SPSS and offer data management solutions that allow researchers to carry out case selection, create derived data and carry out file reshaping. It also provides you with the data documentation which helps the researchers to store metadata in the dictionary.
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The parametric tests are the ones that are merely based on assumptions. There are different variables extracted from the collected population data. It is assumed that the populated data is dispensed. The parameter in terms of statistics would be referred to as a population. If it is not in terms of statistics it is referred to as a sample. Various types of parametric tests that are performed in SPSS include - Student’s T-tests and ANOVA tests.
The parametric test shows the normal distribution of the population. The homogeneity of variance will ensure that various groups will have the same variance.
The opposite to of a parametric test is a non-parametric test which will not have any assumptions related to the population parameters. Various types of non-parametric tests that are carried out in SPSS include - chi-square, Fisher’s exact test, and the Mann-Whitney test. Every parametric test that you carry out will have a non-parametric parameter. For instance, the parametric data from two different groups can be run independent sample t-tests to do the comparison of their means. In case you have non-parametric data, you can run the Mann-Whitney test.
Analysis of Variance in SPSS will help you to examine the differences that you observe in the mean values of variables that are dependent on that of independent variables after taking the uncontrolled independent variables into consideration. ANOVA in SPSS will be used to test the means of multiple samples or populations. It is essential for ANOVA to have a dependent variable with a metric. ANOVA in SPSS will have one or multiple variables that are independent. The independent variables that are categorized are known as factors. A specific combo of factor levels is known as a treatment. The researcher who would like to do the examination of heavy, light, medium, and non-users of cereals can be differentiated from the total cereal. The difference is easier to examine using the ANOVA test in SPSS. Learn all such ANOVA concepts by seeking SPSS homework help from us.
SPSS modeler is also used for data mining and can be used as text analytics software. It is developed using predictive models to carry out analytical tasks. The visually rich interface will let you take advantage of the statistics along with data mining algorithms without having any programming knowledge. SPSS will make use of a strategic approach to establish relationships between large datasets.
SPSS forecasting is the most critical part of the time series module. It has a lot of observations that are gathered with the measurement of a single variable over a period. It uses the model that helps you to predict future events based on the events that happened in the past.
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SPSS is a powerful statistical software that is used for editing as well as analyzing different data sets. The data will be gathered from various sources such as customer databases, Google Analytics, research, or from the log files of different websites. The best thing about SPSS is that it has the capability to open the file in different formats and these are structured in a spreadsheet, relational database, STATA, SAS, and plain text files.
The key features of SPSS are that you can open data files in different formats, and edit data by computing sums and meaning rows or columns. It allows you to create tables and charts. You can run inferential statistics for doing regression, factor, and ANOVA analysis.
|IBM SPSS Statistics||Chi-squared test|
|Factor analysis test||Spearman`s rank correlation test|
|Time series analysis test||Students` t-test|
|Multiple Linear Regression analysis||Mann-Whitney u test|
|Analysis of variance (ANOVA)||Principal Component Analysis|
|Logistics Regression||Design of Experiments|
|Statistical Inference||Applied Econometrics|
|Biostatistics||Statistical Process Control|
|Friedman Test||Nonparametric Models|
|Panel Data Analysis||Discriminant Function Analysis|
|Canonical Correlation Analysis||SPSS Chart Builder|
|Kruskal-Wallis Test||Multivariate Analysis of Variance (MANOVA)|
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