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What statistics analysis is included in SPSS.  1.Distinct insights: Cross tabulation, Frequencies, Descriptive, Explore, Descriptive Ratio statistics  2.Bivariate insights: Means, t-test, ANOVA, Correlation, Nonparametric tests  3.The expectation for numerical results: Linear relapse  4.The expectation for recognizing gatherings: Factor examination, bunch investigation, Discriminant Write a note on a) Normal Distribution. b) Skewness. c) Kurtosis. A. Normal Distribution.  A normal distribution will be bell-shaped and symmetrical. B. Skewness .  Skewness measures the symmetry of the distribution.  Distributions with positive skewness have a longer tail to the right, those with negative skewness have a longer tail to the left. C. Kurtosis .  Kurtosis refers to the peak of the distribution.  More peaked distributions have positive kurtosis.  Flatter distributions have negative kurtosis. Write the steps to be performed to get Correlation coefficients In SPSS . 1. Click on Analyze\Correlate\Bivariate. 2. Select your two variables and move them into the box Variables. 3. In the Correlation Coefficients section, Pearson is the default option. If you wish to request the Spearman rho, tick the Spearman box as well. 4. Under Options, click on the Exclude cases pairwise box. 5. Click on Continue, then OK. What are the advantages and disadvantages of SPSS. Advantages. 1. Easy to learn and use 2. Handles big datasets 3. Can save datasets into numerous file extensions 4. Facilitates import and export of different files 5. Many complex statistical tests are available as a built in feature. 6. Interpretation of results is relatively easy. 7. Easily and quickly displays data tables. 8. Can be expanded. Disadvantages. 1. SPSS can be expensive to purchase for students. 2. Usually involves added training to completely exploit all the available features. 3. The graph features are not as simple as of Microsoft Excel. Elaborate scale measurements used in SPSS. A) Nominal.  1.A nominal variable is a variable whose values don't have a definite order.  2.Categorical data where there is no inherent order to the categories. For example, a job category of sales is not higher or lower than a job category of marketing or research.  3.Nominal scale is a naming scale, where variables are simply “named” or labeled, with no specific order. B.Ordinal.  1.Ordinal variables hold values that have an undisputable order but no fixed unit of measurement. 2. Categorical data where there is a meaningful order of categories, but there is not a measurable distance between categories. C.Scale.  Data measured on an interval or ratio scale, where the data values indicate both the order of values and the distance between values. D.Interval Variables  Interval variables have a fixed unit of measurement but zero does not mean “nothing”. E.Ratio Variables  Ratio variables have a fixed unit of measurement and zero really means “nothing.” Interpret the following SPSS Correlation output given below. A.Pearson’s r  1.The first is the value of Pearson’ r – i.e., the correlation coefficient. That’s the Pearson correlation figure (inside the square red box, above), which in this case is .094. 2. Pearson’s r varies between +1 and -1, where +1 is a perfect positive correlation, and -1 is a perfect negative correlation. 0 means there is no linear correlation at all.  3.Our figure of .094 indicates a very weak positive correlation. The more time that people spend doing the test, the better they’re likely to do, but the effect is very small. B.Significance  1.We’re also interested in the 2-tailed significance value – which in this case is < .000 . The standard alpha value is .05, which means that our correlation is highly significant, not just a function of random sampling error, etc.