Become an SPSS Analyst

EDUCBA presents Become an SPSS Analyst

Become an SPSS Analyst

Course Description

7 high-quality and relevant video-based Courses with 14+ hours of well designed, well-crafted study materials on SPSS, Descriptive Statistics, Correlation Techniques, Scatter Plot, Linear Regression, T-Value, Regression Equation, MS Excel, Multiple Regression Modeling, Logistic Regression, Multinomial Regression, Statistical Analysis, Basic Data Management, Correlation Analysis. Learn by doing. Verifiable Certificate of Completion for Courses. Full Lifetime Access. Begin your path towards becoming a professional data consultant to several research studies. Learn how to gather, organizes and statistically analyzes research data. Refines your role as a Statistical Data Analysis Manager or higher level researcher in the corporate world. The focus of current training program will be to help participants learn statistical skills thro... Read More »

7 high-quality and relevant video-based Courses with 14+ hours of well designed, well-crafted study materials on SPSS, Descriptive Statistics, Correlation Techniques, Scatter Plot, Linear Regression, T-Value, Regression Equation, MS Excel, Multiple Regression Modeling, Logistic Regression, Multinomial Regression, Statistical Analysis, Basic Data Management, Correlation Analysis. Learn by doing. Verifiable Certificate of Completion for Courses. Full Lifetime Access.

Begin your path towards becoming a professional data consultant to several research studies. Learn how to gather, organizes and statistically analyzes research data. Refines your role as a Statistical Data Analysis Manager or higher level researcher in the corporate world. The focus of current training program will be to help participants learn statistical skills through exploring SPSS and its different options. The focus will be to develop practical skills of analyzing data, developing an independent capacity to accurately decide what statistical tests will be appropriate with a particular kind of research objective.

On completion of this course you will develop an ability to independently analyze and treat data, plan and carry out new research work based on your research interest. The course encompasses most of the major type of research techniques employed in academic and professional research in most comprehensive, in-depth and stepwise manner.

Over the years, EDUCBA has become the training standard for professional services firms, business professionals, and undergraduate and graduate students. Our extremely practical high-quality video library of courses serve professionals and students from all the leading global firms and top Institutes.

The following courses are included in this bundle:

  • SPSS:01 – Descriptive Statistics
  • SPSS:02 – Correlation Techniques
  • SPSS:03 – Linear Regression Modeling
  • SPSS:04 – Multiple Regression Modeling
  • SPSS:05 – Logistic Regression
  • SPSS:06 – Multinomial Regression
  • SPSS Training Courses – Analyze Data for Statistical Analysis
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Course Details:

Target Audience


  • Students

  • Quantitative and Predictive Modellers and Professionals

  • CFA's and Equity Research professionals

  • Pharma and research scientists

Access Timeframe

Lifetime

Prerequisites

  • Prior knowledge of Quantitative Methods
Certificate Info:

Type of Certification

Certificate of Completion

Format of Certification

Digital

Professional Association/Affiliation

Certificates are recognized by EDUCBA

Method of Obtaining Certification

Upon successful completion of a course, the learner can download their certificate from their Learner Dashboard.

Course Outline

Predictive modelling course aims to provide and enhance predictive modelling skills across business sectors/domains. Quantitative methods and predictive modelling concepts could be extensively used in understanding the current customer behavior, financial markets movements, and studying tests and effects in medicine and in pharma sectors after drugs are administered. The course picks theoretical and practical datasets for predictive analysis.

The course works across multiple software packages such as SPSS, MS Office, PDF writers, and Paint. This course is to specifically learn about Descriptive Statistics, Means, Standard Deviation and T-test Understanding Means, Standard Deviation, Skewness, Kurtosis and T-test concepts. Through this course we are going to understand:
  • Interpretation of descriptive statistics and t- values
  • Implementation on example/sample datasets using SPSS
Predictive modelling course aims to provide and enhance predictive modelling skills across business sectors/domains. Quantitative methods and predictive modelling concepts could be extensively used in understanding the current customer behaviour, financial markets movements, and studying tests and effects in medicine and in pharma sectors after drugs are administered. The course picks theoretical and practical datasets for predictive analysis.

The course works across multiple software packages such as SPSS, MS Office, PDF writers, and Paint.Through this course we are going to understand how correlation techniques explain relationships across variables and are important in explain the model fitment in regression courses.Particularly we shall be understanding basic correlation theory and understanding positive, negative and zero correlation. Through this course we are going to understand:
  • Interpretation of correlation values for predicting current relationships
  • Implementation on sample datasets using SPSS
Predictive modelling course aims to provide and enhance predictive modelling skills across business sectors/domains. Quantitative methods and predictive modelling concepts could be extensively used in understanding the current customer behaviour, financial markets movements, and studying tests and effects in medicine and in pharma sectors after drugs are administered. The course picks theoretical and practical datasets for predictive analysis.

The course works across multiple software packages such as SPSS, MS Office, PDF writers, and Paint.Regression modelling forms the core of Predictive modelling course. The core objective of this course is to provide skills in understand the regression model and interpreting it for predictions. The associated parameters of the regression model will be interpreted and tested for significance and test the goodness of fit of the given regression model. Through this course we are going to understand:
  • Interpretation of regression attributes such as R-Squared (correlation coefficient), t and p values
  • m (slope) and c (intercept),
  • dependent (Y) and independent (X) variables
  • Examining the significance of independent (X) variable to check the fitness of regression model
  • Predicting Y-variable based on varying values of X-variable
  • Implementation on sample datasets using SPSS and output simulation in MS Excel
Predictive modelling course aims to provide and enhance predictive modelling skills across business sectors/domains. Quantitative methods and predictive modelling concepts could be extensively used in understanding the current customer behaviour, financial markets movements, and studying tests and effects in medicine and in pharma sectors after drugs are administered. The course picks theoretical and practical datasets for predictive analysis.

The course works across multiple software packages such as SPSS, MS Office, PDF writers, and Paint.Regression modelling forms the core of Predictive modelling course. The core objective of this course is to provide skills in understand the regression model and interpreting it for predictions. The associated parameters of the regression model will be interpreted and tested for significance and test the goodness of fit of the given regression model. Through this course we are going to understand:
  • Interpretation of regression attributes such as R-Squared (correlation coefficient), t and p values
  • m (slope) and c (intercept),
  • Dependent (Y) variables and independent (X1, X2, X3……) variables
  • Examining significance/relevance of X-variables in regression model (equations) for goodness of fit of regression model
  • Predicting Y-variable upon varying values of X-variables
  • Understanding Multi-Collinearity and its disadvantages
  • Implementation on sample datasets using SPSS and output simulation in MS Excel
Predictive modelling course aims to provide and enhance predictive modelling skills across business sectors/domains. Quantitative methods and predictive modelling concepts could be extensively used in understanding the current customer behavior, financial markets movements, and studying tests and effects in medicine and in pharma sectors after drugs are administered. The course picks theoretical and practical datasets for predictive analysis.

The course works across multiple software packages such as SPSS, MS Office, PDF writers, and Paint.Regression modelling forms the core of Predictive modelling course. The core objective of this course is to provide skills in understand the regression model and interpreting it for predictions. The associated parameters of the regression model will be interpreted and tested for significance and test the goodness of fit of the given regression model. Through this course we are going to understand:
  • Interpretation of regression attributes such as R-Squared (correlation coefficient), t and p values
  • m (slope) and c (intercept),
  • Dependent (Y) variables and independent (X1, X2, X3……) variables
  • Examining significance/relevance of X-variables in regression model (equations) for goodness of fit of regression model
  • Predicting Y-variable upon varying values of X-variables
  • Understanding Multi-Collinearity and its disadvantages
  • Implementation on sample datasets using SPSS and output simulation in MS Excel
Predictive modelling course aims to provide and enhance predictive modelling skills across business sectors/domains. Quantitative methods and predictive modelling concepts could be extensively used in understanding the current customer behavior, financial markets movements, and studying tests and effects in medicine and in pharma sectors after drugs are administered. The course picks theoretical and practical datasets for predictive analysis. The course works across multiple software packages such as SPSS, MS Office, PDF writers, and Paint.

Regression modelling forms the core of Predictive modelling course. The core objective of this course is to provide skills in understand the regression model and interpreting it for predictions. The associated parameters of the regression model will be interpreted and tested for significance and test the goodness of fit of the given regression model. Through this course we are going to understand:
  • Interpretation of regression attributes such as R-Squared (correlation coefficient), t and p values
  • m (slope) and c (intercept),
  • Dependent variables (Y), independent (X1, X2, Xn ……) variables, and Binary/Dummy B1, B2, B3 …..) variables
  • Examining significance/relevance of X, B variables for regression model (equation) goodness of fit
  • Predicting Y-variable upon varying values of A, B variables
  • Implementation on sample datasets using SPSS and output simulation in MS Excel
SPSS is a widely used windows based program which is used for statistical analysis which helps to perform data entry and analysis to create tables and graphs. It is a comprehensive and flexible data management and statistical analysis solution. SPSS training is a statistical package which is used for beginning, intermediate and advanced data analysis.

Technical Requirements

  • MS Office and Paint is desired

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