Project – Hypothesis Testing using R Online Course

Project – Hypothesis Testing using R Online Course

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• Hypothesis Testing In r Training Courses
  

  Hypothesis testing refers to a process wherein an analyst tests a statistical hypothesis. The nature of the data and goal of analysis affect the methodology employed by the analyst/researcher. The basic goal of each researcher is to accept or reject the hypothesis, based on the measurements of observed samples. The decision, which is based on a statistical mechanism, is referred to as Hypothesis Testing. They have real world applicability and implications and assist in analyzing most collection of data.

  
  Course Description
  

  eduCBA’s course on Hypothesis testing is a small course for all those interested and having an inclination towards dealing in statistical data. This course shall help one draw conclusions about the population from a sample and making decision in regard to the entire population.

  
  Curriculum
  
  • The first phase in the curriculum involves the basic introduction (to give an overview of the topic), its theory, Parametric and non-parametric tests.
  • The second phase shall involve the various types of hypothesis and the type one, type two errors.
  • The type one error is the incorrect rejection of a true null hypothesis.
  • The type two error is the failure to reject a falsified null hypothesis.
  • The third phase is the practical stage which involves complete understanding of the entire concept. It involves the steps in doing hypothesis testing.
  • Seven steps in doing hypothesis testing and finding the p value. It shall involve making a decision to accept or reject on the basis of the values found
  • After decision to accept or reject is made, the next step is to conduct one or two hypothesis tests to be able to confirm upon the decision so taken
  • F test in R with its coding and examples
  • T test in R with its codes and examples
  • Z test in R with its codes and examples
  • Linear regression vs. anova testing
  • One way anova data
  • Plotting and interpretation of anova data
  • The basics of simple and multiple linear regression basics
  • Explanation to linear datasets in R
  • Decision of various assumptions to be taken under linear regression
  • Simple and multiple linear regression in R

  All these steps give an insight into what the course would exactly be like. It shall provide an in depth knowledge about each step written and shall make one an expert in the field of hypothesis testing.

Certificate of completion

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Project – Hypothesis Testing using R Online Course

Hypothesis testing refers to a process wherein an analyst tests a statistical hypothesis. The nature of the data and goal of analysis affect the methodology employed by the analyst/researcher. The basic goal of each researcher is to accept or reject the hypothesis, based on the measurements of observed samples. The decision, which is based on a statistical mechanism, is referred to as Hypothesis Testing. They have real world applicability and implications and assist in analyzing most collection of data.

Course Description

eduCBA’s course on Hypothesis testing is a small course for all those interested and having an inclination towards dealing in statistical data. This course shall help one draw conclusions about the population from a sample and making decision in regard to the entire population.

Curriculum

• The first phase in the curriculum involves the basic introduction (to give an overview of the topic), its theory, Parametric and non-parametric tests.
• The second phase shall involve the various types of hypothesis and the type one, type two errors.
• The type one error is the incorrect rejection of a true null hypothesis.
• The type two error is the failure to reject a falsified null hypothesis.
• The third phase is the practical stage which involves complete understanding of the entire concept. It involves the steps in doing hypothesis testing.
• Seven steps in doing hypothesis testing and finding the p value. It shall involve making a decision to accept or reject on the basis of the values found
• After decision to accept or reject is made, the next step is to conduct one or two hypothesis tests to be able to confirm upon the decision so taken
• F test in R with its coding and examples
• T test in R with its codes and examples
• Z test in R with its codes and examples
• Linear regression vs. anova testing
• One way anova data
• Plotting and interpretation of anova data
• The basics of simple and multiple linear regression basics
• Explanation to linear datasets in R
• Decision of various assumptions to be taken under linear regression
• Simple and multiple linear regression in R

All these steps give an insight into what the course would exactly be like. It shall provide an in depth knowledge about each step written and shall make one an expert in the field of hypothesis testing.

In the technological world, one cannot stay delinked with technology in any field. Hypothesis testing being no exception to it either, the course demands basic knowledge of internet usage and computer handling. Hence, it requires easy accessibility to technology for the purpose of carrying out various tests and keeping a store of all the information gathered from various sample sources.

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