Condition of T-test used
Test of significance of a single mean.$$\frac{\overline{X}-µ}{\sqrt{\frac{s^2}{n}}}∼t_n=1$$ $$\frac{\overline{X}-µ}{\sqrt{\frac{s^2}{n-1}}}∼t_n=1$$ $$where\,\overline{X_1}=mean\,of\,first\,sample=\frac{∑X_1}{n}$$
Summary
Test of significance of a single mean.$$\frac{\overline{X}-µ}{\sqrt{\frac{s^2}{n}}}∼t_n=1$$ $$\frac{\overline{X}-µ}{\sqrt{\frac{s^2}{n-1}}}∼t_n=1$$ $$where\,\overline{X_1}=mean\,of\,first\,sample=\frac{∑X_1}{n}$$
Things to Remember
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$$t=\frac{Difference}{S.E\overline{(X)}}$$
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$$\frac{\overline{X}-µ}{\frac{s}{\sqrt{n}}}$$
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$$\frac{\overline{X}-µ}{\sqrt{\frac{s^2}{n}}}∼t_n=1$$
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Condition of T-test used
Test of significance of a single mean.
Under H0, the test statistic is.
$$t=\frac{Difference}{S.E\overline{(X)}}$$
$$\frac{\overline{X}-µ}{\frac{s}{\sqrt{n}}}$$
$$\frac{\overline{X}-µ}{\sqrt{\frac{s^2}{n}}}∼t_n=1$$
and it followa students t-distribution with (n-1)degree of freedom
$$\overline{X}=Sample\,mean=\frac{∑X}{n}$$
$$S^2=an\,unbiased\,estimate\,of\,the\,population\,varience\,and\,it\,is\,computed by$$
1. Actual mean method.
$$S^2=\frac{1}{n-1}∑(X-\overline{X})^2$$
$$=\frac{1}{n-1}(∑X^2-n\overline{X^2})$$
This is application when the mean value is in whole number.
2.Direct method.
$$S^2=\frac{1}{n-1}[∑X^2-n∑\overline{X^2}]$$
$$S^2=\frac{1}{n-1}[∑X^2-\frac{(∑X)^2}{n}$$
$$\frac{(∑X)^2}{n}$$
This is applicable when the mean value is in fractional form and the data are given at most two digits.
3. Shortcut or assumed mean method
$$S^2=\frac{1}{n-1}∑X^2-\frac{(∑X)^2}{n}$$
$$where\,d=X-A$$
$$and\,\overline{X}=A+\frac{∑d}{n};A=assumed\,mean$$
when the biased estimate of the population variance i,e s2 or standard deviation 's' given then the value of t is computed by.
$$\frac{\overline{X}-µ}{\sqrt{\frac{s^2}{n-1}}}∼t_n=1$$
$$\frac{\overline{X}-µ}{\sqrt{\frac{s^2}{n-1}}}∼t_n=1$$
$$where\,sample\,variance\,S^2=\frac{1}{n}∑(X-\overline{X})^2$$
$$=\frac{1}{n}[∑X^2-n\overline{X^2}]$$
$$\frac{∑X^2}{n}-\frac{(∑X)}{n}^2$$
Test of significance of a difference between two means.
Under the assumption thatσ12=σ22=σ2 i,e population variances are equal but unknown the test statistics under H0:µ1=µ2 is
i,e the test statistic t follows t-distribution with n1+n2-Z degree of freedom.
$$where\,\overline{X_1}=mean\,of\,first\,sample=\frac{∑X_1}{n}$$
$$where\,\overline{X_2}=mean\,of\,first\,sample=\frac{∑X_2}{n}$$
$$S_p^2=an\,unbiased\,estimate\,of\,the\,common\,population\,variance\,and\,its\,value\,is\,computed\,by\,the\,following\,methods$$
Reference
Kerlinger, F.N. Foundation of Behavioural Research. New Delhi: Surjeet Publication, 2000.
Kothari, C.R. Research Methodology. India: Vishwa Prakashan, 1990.
Singh, M.L. and J.M Singh. Understanding Research Methodology. 1998.
Singh, Mrigendra Lal. Understanding Research Methodology. Nepal: National Book centre, 2013.
Lesson
Principal Methods of Analysis and Interpretation
Subject
Research Methodology-II
Grade
Bachelor of Science
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