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Research And Data Analysis

Table of content

TABLE OF CONTENT 1
INTRODUCTION 2
Statistical Hypotheses: 2
Null Hypothesis: 2
TYPES OF TESTS 2
ERROR 3
STEPS IN HYPOTHESIS TESTING 4
PRACTICAL EXAMPLES 5
LIMITATIONS FOR ENVIRONMENTAL SAMPLING 8
SUMMARIZE 9
FREQUENCIES 10
HISTOGRAM 12
DATA VIEW FROM SPSS 14
VARIABLE VIEW FROM SPSS 15

Introduction

There are two types of statistical inferences: estimation of population parameters and hypothesis testing. Hypothesis testing is one of the most important tools of application of statistics to real life problems. Most often, decisions are required to be made concerning populations on the basis of sample information. Statistical tests are used in arriving at these decisions.
Statistical Hypotheses:
They are defined as assertion or conjecture about the parameter or parameters of a population, for example the mean or the variance of a normal population. They may also concern the type, nature or probability distribution of the population.
Statistical hypotheses are based on the concept of proof by contradiction. For example, say, we test the mean (δ) of a population to see if an experiment has caused an increase or decrease in δ. We do this by proof of contradiction by formulating a null hypothesis.
Null Hypothesis:
It is a hypothesis which states that there is no difference between the procedures and is denoted by H0. For the above example the corresponding H0 would be that there has been no increase or decrease in the mean. Always the null hypothesis is tested, i.e., we want to either accept or reject the null hypothesis because we have information only for the null hypothesis.
Types of Tests

Tests of hypothesis can be carried out on one or two samples. One sample tests are used to test if the population parameter (δ) is different from a specified value. Two sample tests are used to detect the difference between the parameters of two populations (δ1 and δ2).
Two sample tests can further be classified as unpaired or paired...