Best Spss Training Institute & Certification in Noida

Live Project Based Spss Programming training in Noida

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KVCH is the pioneer of education providing the�best Spss Programming training in Noida�as per the current industry requirement that enables candidates to land on their dream jobs in companies worldwide. KVCH Provides best Spss Programming training course in Noida. KVCH is a renowned training company providing the best training service and also being the best Spss Programming training institute in Noida rendering practical knowledge through training on projects and a dedicated placement assistance for all.�The course curriculum for Spss Programming training course is designed to provide in-depth knowledge that covers all the modules for the training ranging from basic to advanced level. At KVCH Spss Programming training in Noida is supervised and managed by industrial experts having more than 10 years of experience in handling Spss Programming projects. KVCH training comprises of both classroom as well as practical sessions to deliver an ideal environment for students that will enable them to handle difficult and complex situation when they would step into the reality of IT sector.

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Spss Programming training course involves "Hands-on experience", we believe in practice what you preach and therefore each candidate is encouraged to practically conduct each topic that is discussed for better understanding of real-world scenar Spss Programming. This practice of comprehensive training allows candidate to gain all the concepts and skills effectively and to later efficiently apply on their field of work.

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Accredited Curriculum

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SPSS Programming

Research methods :

Statistics?
The Research Process
Initial Observation
Generate Theory
Generate Hypotheses
Data collection to Test Theory
What to measure
How to Measure
Analyze data
Descriptive Statistics: Overview
Central Tendency
Measure of variation
Coefficient of Variation
Fitting Statistical Models
Conclusion

Statistics :

Building statistical models
Types of statistical models
Populations and samples
Simple statistical models
The mean as a model
The variance and standard deviation
Central Limit Theorem
The standard error
Confidence Intervals
Test statistics
Non-significant results and Significant results
One- and two-tailed tests
Type I and Type II errors
Effect Sizes
Statistical power

SPSS Environment :

Accessing SPSS
To explore the key windows in SPSS
Data editor
The viewer
The syntax editor
How to create variables
Enter Data and adjust the properties of your variables
How to Load Files and Save
Opening Excel Files
Recoding Variables
Deleting/Inserting a Case or a Column
Selecting Cases
Using SPSS Help

Exploring data with graphs :

The art of presenting data
The SPSS Chart Builder
Histograms: a good way to spot obvious problems
Boxplots (box�whisker diagrams)
Graphing means: bar charts and error bars
Simple bar charts for independent means
Clustered bar charts for independent means
Simple bar charts for related means
Clustered bar charts for related means
Clustered bar charts for �mixed� designs
Line charts
Graphing relationships: the scatterplot
Simple scatterplot
Grouped scatterplot
Simple and grouped -D scatterplots
Matrix scatterplot
Simple dot plot or density plot
Drop-line graph
Simple scatterplot
Editing graphs

Exploring assumptions :

What are assumptions?
Assumptions of parametric data
The assumption of normality
Quantifying normality with numbers
Exploring groups of data
Testing whether a distribution is normal
Kolmogorov�Smirnov test on SPSS
Output from the explore procedure
Reporting the K�S test
Testing for homogeneity of variance
Levene�s test
Reporting Levene�s test
Correcting problems in the data
Dealing with outliers
Dealing with non-normality and unequal variances
Transforming the data using SPSS

Correlation :

Looking at relationships
How do we measure relationships?
Covariance
Standardization and the correlation coefficient
The significance of the correlation coefficient
Confidence intervals for r
Correlation in SPSS
Bivariate correlation
Pearson�s correlation coefficient
Spearman�s correlation coefficient
Kendall�s tau (non-parametric)
Biserial and point�biserial correlations
Partial correlation
The theory behind part and partial correlation
Partial correlation using SPSS
Semi-partial (or part) correlations
Comparing correlations
Comparing independent rs
dependent rs
Calculating the effect size
How to report correlation coefficients

Regression:

An introduction to regression
Some important information about straight lines
The method of least squares
Assessing the goodness of fit: sums of squares, R and R2
Doing simple regression on SPSS
Interpreting a simple regression
Overall fit of the model
Model parameters
Using the model
Multiple regression: the basics
An example of a multiple regression model
Sums of squares, R and R2
Methods of regression
How accurate is my regression model?
Assessing the regression model I: diagnostics
Assessing the regression model II: generalization
How to do multiple regression using SPSS
Some things to think about before the analysis
Main options
Statistics
Regression plots
Saving regression diagnostics
Interpreting multiple regression
Descriptive
Summary of model
Model parameters
Excluded variables
Assessing the assumption of no multicollinearity
Casewise diagnostics
Checking assumptions
What if I violate an assumption?
to report multiple regression

Categorical predictor in multiple regression :

Dummy coding
SPSS output for dummy variables

Logistic regression :

Background to logistic regression
What are the principles behind logistic regression?
Assessing the model: the log-likelihood statistic
Assessing the model: R and R2
The Wald statistic
The odds ratio: Exp (B)
Methods of logistic regression
Assumptions
Incomplete information from the predictors
Complete separation
Overdispersion
Binary logistic regression
The main analysis
Method of regression
Categorical predictors
Obtaining residuals
Interpreting logistic regression
The initial model
Step: intervention
Listing predicted probabilities
Interpreting residuals
Calculating the effect size
How to report logistic regression
Testing assumptions
Testing for linearity of the logit
Predicting several categories: multinomial logistic regression
Running multinomial logistic regression in SPSS
Statistics
Other options
Interpreting the multinomial logistic regression output
Reporting the results

Comparing two means (t-test) :

Looking at differences
A problem with error bar graphs of repeated-measures designs
Step : calculate the mean for each participant
Step : calculate the grand mean
Step : calculate the adjustment factor
create adjusted values for each variable
The t-test
Rationale for the t-test
Assumptions of the t-test
Sampling distributions and the standard error
The dependent t-test equation explained
The dependent t-test and the assumption of normality
Dependent t-tests using SPSS
Output from the dependent t-test
Calculating the effect
Reporting the dependent t-test
The independent t-test
The independent t-test equation explained
The independent t-test using SPSS
Output from the independent t-test
Calculating the effect size
Reporting the independent t-test
Between groups or repeated measures?
The t-test as a general linear model

Comparing several means: ANOVA (GLM) :

The theory behind ANOVA
Inflated error rates
Interpreting f-test
ANOVA as regression
Logic of the f-ratio
Total sum of squares (SST)
Model sum of squares (SSM)
Residual sum of squares (SSR)
Mean squares
The f-ratio
Assumptions of ANOVA
Planned contrasts
Post hoc procedure
Running one-way ANOVA on SPSS
Planned comparisons using SPSS
Post hoc tests in SPSS
Output from one-way ANOVA
Output for the main analysis
Output for planned comparisons
Output for post hoc tests
Calculating the effect size
Reporting results from one-way independent ANOVA
Violations of assumptions in one-way independent ANOVA

Chi-square :

Analysing categorical data
Theory of analysing categorical data
Pearson�s chi-square test
Fisher�s exact test
The likelihood ratio
Yates� correction
Assumptions of the chi-square test
Doing chi-square on SPSS
Running the analysis
Breaking down a significant chi-square test with standardized residuals
Calculating an effect size
Reporting the results of chi-square

Top Reasons to Choose KVCH for Spss Programming Programming Training in Noida

Spss Programming training in Noida is constructed as per the IT industry standard.
We Offer the best Spss Programming training and dedicated placement assistance in Noida with properly planned training modules and course content.
Regular and Weekends classes for Spss Programming training in Noida is provided.
One of the biggest team of Certified Expert Trainers with 5 to 15 years of Real Industry Experience.
Mentors of Spss Programming training in Noida helps in major project training, minor project training, live project preparation, interview preparation and job placement support.
Smart Labs with Real Latest Equipment�s.
24x7 Lab Facilities. Students are free to access the labs for unlimited number of hours as per their own preferred timings.
Silent and Discussion Zone areas in Labs to enhance Self Study and Group Discussions.
Free of Cost Personality Development sessions including Spoken English, Group Discussions, Mock Interviews, Presentation skills.
Free of Cost Seminars for Personality Development & Personal Presentation.
Varity of Study Material: Books, PDF�s, Video Lectures, Sample questions, Interview Questions (Technical and HR), and Projects.
Hostel Facilities available at Rs. 5,500/month for Spss Programming Training in Noida students.
Free Study Material, PDFs, Video Trainings, Sample Questions, Exam Preparation, Interview Questions, Lab Guides.
Globally Recognized Course Completion Certificate.
Extra Time Slots (E.T.S.) for Practical�s (Unlimited), Absolutely Free.
The ability to retake the class at no-charge as often as desired.
One-on-One attention by instructors.
Helps students to take knowledge of complex technical concepts.
Payment options: Cheque, Cash, Credit Card, Debit card, Net Banking.

KVCH Trainer's Profile for Spss Programming Training in Noida

KVCH'S Spss Programming Trainers are:

Are experts in their field of domain and constantly upgrade themselves with new tools to impart the best training of a real working environment
Have been carefully selected by our training partners and recognized over the years by various organizations for their field of work.
Have years of experience in working in Big corporation and MNC�s like IBM, HCL Technologies, Sapient, Birla soft, TCS, Accenture etc.
Certified Industry Professionals with more than 10+ years of experience in Itindustry.
Connected with placement cells of various companies to help and support students for placement

Placement Assistance after Spss Programming Training in Noida

KVCH'S Placement Assistance

KVCH is the world leader in rendering placement assistance to students with the help of a dedicate placement cell that supports and assists students during the time of placement.
KVCH also provide the best Resume Building Service, by helping students to design their resume as per the latest industry trend.
KVCH regularly organizes Personality Development sessions including Group Discussions, Mock Interviews, Presentation skills that help students in overall personality development and to present themselves confidently at the time of interview.
KVCH has helped students to grab their dream jobs in companies like IBM , HCL , Wipro , TCS , Accenture ,etc.

KVCH Course duration for Spss Programming Training in Noida

Regular Classes� 5 days a week (Morning, Day time & Evening)
Weekend Classes (Saturday, Sunday & Holidays)
Fast-track Classes

TRAINING IN Spss Programming