Address: prashanth complex, 2nd floor venkatadri theater opp , Warangal ,Andhra Pradesh-500060
Address: Flat No:101, H-No: 8-3-809, Priya nivas, Ameerpet, Hyderabad -560018
Address: sai ratna plaza,nagamalli, thota Kakinada, Andhra Pradesh-533003
Address: B1, 3rd Floor, Eureka Court, Ameerpet, Hyderabad-500073.
Address: Incomp Software Technologies, 446 Ayyappa Society, S.Chandra Reddy Tower,First Floor, Madhapur, Hyderabad-500081.
Address: kphb malusian, township circle, Anantapur, Andhra Pradesh-500072
Address: Plot No: 133, Sarada Nagar, Vanasthlipuram, Hyderabad – 500070.
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Learning SPSS course in Andhra Pradesh - Benefits, Advantages & Placements.
We have identified the benefits of learning spss course in Andhra Pradesh.
SPSS training in Andhra Pradesh is part of SAS training course class, SPSS Statistics stands for Statistical Package for the Social Sciences is an integrated family of products that addresses the entire analytical process, from planning to data collection to analysis, reporting and deployment. The software is best suited for any statistical calculations. It can run pretty much any statistical test with a few clicks. The user interface is easy, it is different from others but very intuitive once you are used to it. SPSS is the only one in which it is easy to edit the data or variable properties in the data view. The visualization features of the software are Time series/forecasting, Machine learning, Survival analysis, graphs etc.
Data manipulation is the strong suit of SPSS. The other feature of SPSS that stands out in comparison to other packages is the color coded syntax files that make it very easy to catch and correct errors in your code. Its easier to import a text file into SPSS and export it to Stata than it is to import the text file directly into Stata. The software is useful to read and write data from ASCII text files (including hierarchical files), other statistics packages, spreadsheets and databases.
Some of the statistics included in the software are Descriptive statistics, Bivariate statistics, Prediction for numerical outcomes and Prediction for identifying groups. The several features of the software are accessible via pull-down menus or can be coded with a proprietary 4GL command syntax language. Command syntax programming has the benefits of reproducible output, simplifying repetitive tasks, and handling complex data manipulations and analyses.
The eight largest state of the country. The city is rich in culture and tradition. The state contributes relatively more to the india GDP. The place is so serene that itâ€™s the 3rd most visited place in India by tourist. The state focuses on education and economic development. In the aspects of education many students reside in the state for education as it has many reputed institutions like All India Institute of Medical Sciences, IIM Visakhapatnam, IIT Tirupati, National Institute of Technology Andhra Pradesh and IIITDM Kurnool, Indian Institute of Petroleum and Energy, National Institute of Oceanography, Visakhapatnam (NIO). The state is the home for the famous Indian Space Research Organisation (ISRO) in Nellore district. Many IT and MNCs and core industries have set foot in the state and hence there is a large opportunities in job employment.
You have travel connectivity to spss course educational training institutes in Andhra Pradesh. The APSRTC connects to all the cities and states. The state has national and state highway that connects to other places via roadways. The state has Vishakhapatnam airport operating international flights and the state has 4 domestic airports in Rajhmundry, Renigunta, Cuddapah Airport and a privately owned, public use airport at Puttaparthi. The taxies , auto rickshaws connects to the local areas in the city.
SPSS course Content / syllabus in andhra-pradesh
Below is the SPSS course content in andhra-pradesh used by the training institutes as part of the SPSS course training. The SPSS course syllabus covers basic to advanced level course contents which is used by most of SPSS training classes in andhra-pradesh .
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
Lab Work & Project
All the units will include discussion on theoretical concepts followed by practical SPSS demonstration on real/simulated data. Learners are welcome to bring and discuss their actual problems related to quantitative analysis. Our every learner receives personal attentions and we endeavour to equip every learner to develop a sense of professional competency in quantitative data analysis using SPSS.