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This section of our blog discusses the important techniques used in market research. These techniques help in the development of a mathematical model to various characteristics, behaviors will be in this section also be useful if we know how to predict one’s claim to the right use of statistics, statistical test for market research purposes. We will try to make it as easy as possible in our approach. We hope that it will be of great use to researchers and student community.

Of course we are also the help of SPSS, we will not go into complex math and derivations since it does not make sense behind many of the tests and techniques.

We assume that the reader be familiar with basic statistics such as mean, mode, median. Other things remaining will be discussed as and when necessary

Another thing that we use a uniform 95% confidence interval.

first hypothesis tests
In general it can be very confusing to learn different techniques and tests. The golden rule is that if you see any of these tests are you two things. One is the null hypothesis and the p (sig-value). If the p-value is less than 0.05, your null hypothesis is rejected. So if someone makes a null hypothesis “correlation coefficient = 0 or there is no correlation between the two variables.” If the p-value is less than 0.05, then the null hypothesis is rejected. This implies that there is a correlation between the two variables and their significance is low or high, however, may be important. “
Even if you check for regression coefficients Say our statistical test, says the zero- hypothesis as an “All regression coeff. Are zero, “and we have a p-value> get 0.05. Ie, that” zero-hypothesis is true. “This means that the regression coefficients are not significant. The test to check the entire regression coefficient is called the F-test . If we want to single regression coefficnt we need to get their individual p-values ​​(the “coefficient is zero.” of the T-test of the null hypothesis) is checked to verify. In this case, the golden rule.

Now, let some of the statistical tests. We will examine systematically, where it is applied. How to do these tests with SPSS and how it can be useful in a market research study.

First, we have quantitative data on the tests will study

2 cases are

1 normality assumption and Assumption of homogeneity are satisfied in the data. Do not worry, we will take a test to examine the means. Normality is a bell-shaped curve, while the homogeneity means that the data has constant variance. In general, these assumptions are satisfied by in large data sets themselves.

In these cases, we parametric tests.

2 If the above conditions are not met, we would perform an equivalent non Parametic test.

Parametric Non-Parametric

1 sample t test 1.Sign test / Wilcoxon Signed Rank Test

paired t-test Sign test Wilcoxon Signed Rank Test

2-Sample T Test 2.Mann Whitney U test / Wilcoxon Rank Sum

Kruskal Wallis ANOVA test
First we need to do normality test

1 Plot .. the graphics you see the histogram, it should look like a bell curve (Best Art) look

2 Kolmogorov-Smirnov and Shapiro-Wilk test will tell whether the data is normal (null hypothesis: The data is not normal .. then p> 0.05 means data is normal).. You can test with SPSS.

Watch out for more very soon!
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