Link for download: https://mega.nz/#!SQgzQDIC!AFcx6gC9OjbcnMOTO3sA5QBAMkAAf5DR3IIthDtoErE Mention in comments if you want to know how to use SPSS or any other specific topic to be explained through next video. Cheers. :) Do mention if this works for you. If you follow all the steps, it definitely will work. 👍🏻 ♥️
Link to download IBM SPSS 24 For MAC : http://j.gs/8R0C Name IBM_SPSS_Statistics_24.zip Size 794.4 MB Created on 2016-06-13 01:43:48 Hash f05e36492cccd3b07bee3743fa5fca3f8cab8bd1 Files IBM_SPSS_Statistics_24.zip (794.4 MB) Name: IBM SPSS Statistics Version: 24 Language: Multilingual OS Version: OS X 10.8 or later Includes: Patch IBM SPSS Statistics is a comprehensive set of data and tools for easy predictive analytics use for business users, analysts and statistical programmers. IBM SPSS Advanced Statistics creates more accurate analysis and more reliable conclusions when working with complex relationships. IBM SPSS provides effective techniques to real problems in a variety of disciplines, including medical research, manufacturing, pharmaceuticals and market research. It offers advanced techniques of univariate and multivariate very effective and sophisticated, among which include: Procedures general linear models (GLM) and mixed models Generalized Linear Models (GENLIN), which include widely used statistical models such as linear regression for responses distributed normally, logistic models for binary data and log - linear models for count data. GENLIN also offers various statistical models useful through its own general model formulation. the procedures of generalized estimating equations (GEE) extend models linear generalized to accommodate correlated longitudinal data and clustered data generalized linear mixed models (GLMM) for use with hierarchical data
To join online SPSS Foundation Training at just $10 click here: https://www.udemy.com/spss-statistics-foundation-course-from-scratch-to-advanced/?couponCode=UTUBEHX2017 Syllabus: Unit 1: Developing the familiarity with SPSS Processer Entering data in SPSS editor. Solving the compatibility issues with different types of file. Inserting and defining variables and cases. Managing fonts and labels. Data screening and cleaning. Missing Value Analysis. Sorting, Transposing, Restructuring, Splitting, and Merging. Compute & Recode functions. Visual Binning & Optimal Binning. Research with SPSS (random number generation). Unit 2: Working with descriptive statistics Frequency tables, Using frequency tables for analyzing qualitative data, Explore, Graphical representation of statistical data: histogram (simple vs. clustered), boxplot, line charts, scattorplot (simple, grouped, matrix, drop-line), P-P plots, Q-Q plots, Addressing conditionalities and errors, computing standard scores using SPSS, reporting the descriptive output in APA format. Unit 3: Hypothesis Testing Sample & Population, concept of confidence interval, Testing normality assumption in SPSS, Testing for Skewness and Kurtosis, Kolmogorov–Smirnov test, Test for outliers: Mahalanobis Test, Dealing with the non-normal data, testing for homoscedasticity (Levene’s test) and multicollinearity. Unit 4: Testing the differences between group means t – test (one sample, independent- sample, paired sample), ANOVA-GLM 1 (one way), Post-hoc analysis, Reporting the output in APA format. Unit 5: Correlational Analysis Data entry for correlational analysis, Choice of a suitable correlational coefficient: non-parametric correlation (Kendall’s tau), Parametric correlation (Pearson’s, Spearman’s), Special correlation (Biserial, Point-biserial), Partial and Distance Correlation Unit 6: Regression (Linear & Multiple) The method of Least Squares, Linear modeling, Assessing the goodness of fit, Simple regression, Multiple regression (sum of squares, R and R2 , hierarchical, step-wise), Choosing a method based on your research objectives, checking the accuracy of regression model. Unit 7: Logistic regression, Choosing method (Enter, forward, backward) & covariates, choosing contrast and reference (indicator, Helmert and others), predicted values: probabilities & group membership, Influence statistics: Cook, Leverage values, DfBetas, Residuals (unstandardized, logit, studentized, standardized, devaince), Statics and plot: classification, Hosmer-Lemeshow goodness-of-fit, performing bootstrap, Choosing the right block, interpreting -2loglikelihood, Omnibus test, interpreting contingence and classification table, interpreting Wald statistics and odd ratios. Reporting the output in APA format Unit 8: Non-parametric tests When to use, Assumptions, Comparing two independent conditions (Wilcoxon rank-sum test, Mann-Whitney test), Several independent groups (Kruskal- Wallis test), Comparing two related conditions (Wilcoxon signed-rank test), Several related groups (Friedman’s anova), Post-hoc analysis in non-parametric analysis. Categorical testing: Pearson’s Chi-square test, Fisher’s exact test, Likelihood ratio, Yates’ correction, Loglinear Analysis. Reporting the output in APA format. Unit 9: Factor Analysis Theoretical foundations of factor analysis, Exploratory and Confirmatory factor analysis, testing data sufficiency for EFA & CFA, Principal component Analysis, Factor rotation, factor extraction, using factor analysis for test construction, Interpreting the SPSS output: KMO & Bartlett’s test, initial solutions, correlation matrix, anti-image, explaining the total variance, communalities, eigen-values, scree plot, rotated component matrix, component transformation matrix, factor naming Unit 10: Structural Equation Modelling using IBM AMOS Getting familiar with AMOS graphics, defining the variables-endogeneous, exogeneous, residual; Model building, Meeting the assumptions of SEM, Dealing with the non-normal data, Bootstrapping, detecting the outliers-Mahalanobis Distance Mediation Analysis, Indirect and Direct Effects, Testing the EFA model for surveys and tests, Explaining the model-p values, estimates, standard error, critical ratio, Understanding the indices of model fit- chi square, relative chi square, GFI, AGFI, PGFI, SRMR, NFI, TLI, CFI, RMSEA; Registration: For registration in classroom course and any other details contact firstname.lastname@example.org Program date: Summer batch: Second week of May Winter Batch: Second week of December Fee for classroom course: $100 if registered 3 months advance for both batch else $ 250. Group discount available.
VIDEO SECTIONS: 0:30 – Preparing a Data Set 10:51 – Transforming Data 17:49 – Descriptive Statistics 29:25 – SPSS Syntax Editor
This video will guide you through the process of downloading and installing your SPSS Grad Pack v25 for Mac after purchasing from Hearne Software.
STA10003 Installing SPSS 21 for Mac This video shows you how to install SPSS 21 for Mac either via a disk or from a download from onthehub.com
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Updated video 2018: SPSS for Beginners - Introduction https://youtu.be/_zFBUfZEBWQ This video provides an introduction to SPSS/PASW. It shows how to navigate between Data View and Variable View, and shows how to modify properties of variables.
This video is about installing SPSS Statistic in Mac OS X Sierra
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