STATISTICS-SESSION 9 AND 10

CHI SQUARE ANALYSIS AND NULL HYPOTHESIS

                                                                                                                                                              The chi-square test for independence, also called Pearson's chi-square test or the chi-square test of association, is used to discover if there is a relationship between two categorical variables.

This test allows us to compare a collection of categorical data with some theoretical expected distribution. This test is often used in genetics to compare the results of a cross with the theoretical distribution based on genetic theory. Suppose you preformed a simple monohybrid cross between two individuals that were heterozygotes for the trait of interest.

 

Cross-tabulation analysis has its own unique language, using terms such as “banners”, “stubs”, “Chi-Square Statistic” and “Expected Values.”

OUTPUT:

NULL HYPOTHESIS:

Hypothesis testing works by collecting data and measuring how likely the particular set of data is, assuming the null hypothesis is true. If the data-set is very unlikely, defined as being part of a class of sets of data that only rarely will be observed, the experimenter rejects the null hypothesis concluding it (probably) is false.

  If significant value is less than 0.05 then null hypothesis will not be considered.Now we can said that there is relationship between services &stores.In routine business,significant value is around 0.05.

 Correlation:

Correlation is computed into what is known as the correlation coefficient, which ranges between -1 and +1. Perfect positive correlation (a correlation co-efficient of +1) implies that as one security moves, either up or down, the other security will move in lockstep, in the same direction. Alternatively, perfect negative correlation means that if one security moves in either direction the security that is perfectly negatively correlated will move in the opposite direction. If the correlation is 0, the movements of the securities are said to have no correlation; they are completely random. 

In real life, perfectly correlated securities are rare, rather you will find securities with some degree of correlation.

SUBMITTED BY:PALAK JAIN

GROUP  MEMBERS:

NIDHI 

NITESH SINGH PATEL

NITESH BORATWAR

PALLAVI BIZOARA