# Primary Data vs Secondary Data – Statistics (Similarities and Differences between Primary Data and Secondary Data)

The data is a set of values of qualitative or quantitative variables. In statistics, the data are the individual observations. The scientific investigations involve observations on variables. The observations made on these variables are obtained in the form of ‘data’.

Based on the source, the data is categorized into TWO types: (1) Primary Data and (2) Secondary Data.

Primary Data: Data collected for the first time by the original investigator.

Secondary Data: The data used in statistical investigations which have already been collected by some other for their purpose and published.

The present post discusses the Differences between Primary Data and Secondary Data with a Comparison Table.

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# CSIR JRF NET Life Sciences June, 2018 Solved Question Paper PDF

Official / Original Previous Year (Old) Solved Question Paper of CSIR Junior Research Fellowship (JRF) and National Eligibility Test (NET) Life Sciences (XL) Examination June 2018  with Answer Key as PDF. CSIR aspirants can download the question paper as single PDF file for your exam preparation. To download the question paper, please click on the download link below the PDF preview. Please inform the Admin if you find any mistake in the answer key.

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To download the question paper as a single PDF file, please click on the link below.

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# Types of Experimental Designs in Statistics Completely Randomized Design (CRD), Randomized Block Design (RBD), Latin Square Design (LSD) – Advantages and Disadvantages

In the previous post, we have discussed the Principles of Experimental Designs. There we discussed the concept of Experimental design in statistics and their applications. In the present post, we will discuss different types of statistical experimental designs, its applications, advantages and limitations.

Learn more: Principles of Experimental Designs

## Different types of Experimental Designs

Ø  Experimental designs are broadly classified into TWO categories:

(A).   Single-Factor Experiments

(B).  Multi-factor Experiments

(A). Single-Factor Experiments:

Ø  Single factor experiments are those experiments in which only a single factor varies while all others are kept constant.

Ø  Here the treatments consist exclusively of the different levels of the single variable factor.

Ø  All other factors are applied uniformly to all plots.

Ø  Examples of Single-Factor Experimental Designs:

(1). Completely Randomized Design (CRD)

(2). Randomized Block Design (RBD)

(3). Latin-Square Design (LSD)

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# Experimental Designs in Statistics (The Principles of Experimental Designs in Research Methodology)

What is a statistical experiment?

Ø  An experiment is a plan for the collection and analysis of data.

Ø  “It is a controlled act through which data are collected according to some pre-determined objective”.

Ø The observations obtained from a carefully planned and well-designed experiment in advance only gives valid inferences.

Ø An experimental design which gives the smallest error is supposed to be the best design for a particular type of investigation.

Experimental unit (Experimental Plot):

Ø  The smallest division of the experimental material to which we apply the treatment and can make the observation on it is called experimental unit or experimental plot

Treatments:

Ø  Treatments are the characteristics which are to be investigated through an experiment.

Ø  The treatments are the objects of comparisons in an experiment.

Ø  Example: effects of different fertilizers, the yield of different varieties of a crop, disease resistance of different cultivars etc.

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# Statistical Hypothesis Testing PPT (The Test of Hypothesis / Significance – Tips and Procedure)

What is Hypothesis Testing? What is Test Statistic? Statistical Hypothesis, p-Value, What is ‘Test of Hypothesis’, What is the purpose of Hypothesis Testing? What is Hypothesis? Types of Hypothesis, Research Hypothesis, Statistical Hypothesis, Null Hypothesis, Alternative Hypothesis, How to state the statistical hypothesis? Things to remember when constructing the Null Hypothesis, Test Statistic, Decision Rule, Significance Level, Statistical Decision, p-Value

Learn more: Lecture Note on Hypothesis Testing

You can DOWNLOAD the PPT by clicking on the download link below the preview…

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