# F-test and Chi-Square Test Assignment Help

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## Best F-test and Chi-Square Test Assignment Help

An Introduction to F-test and Chi-Square Test

F-test is a statistical test wherein the test has F-distribution under the null hypothesis. It is commonly used for comparing the statistical models and it should be structured around data for identifying the model that suits the population the best. Chi-square test is a simple and a non-parametric test used in statistical work. Greek letter x2 denotes this test. X2describes the theory of discrepancy and observation. Students pursuing Statistics avail professional F-test and Chi-Square Test assignment help from BookMyEssay because they find this statistical topic a complicated one. Our online tutors help the students to achieve good grades in their academics.

We have employed the best Statisticians who have many years of industry experience and so they apply the updated statistical techniques while writing the statistics assignment. F-test distribution can be formed by the using the ratios of the independent variables of chi-square. The two terms are then divided by their respective degrees. As Ch-Square forms F, F-distribution has many properties of Chi-Square. This topic requires in-depth understanding and therefore, we at BookMyEssay, have hired the Statisticians who possess Ph.D. degree. As our writers have vast industry knowledge they use the advanced level analysis for the F-test and Chi-Square Test homework and assignment help.

## Quality of  F-test and Chi-Square Test

F-test is used for testing the equality of two variances in the population most of the independent normal populations. The two population variances that are equal uses F-distribution with degrees of freedom. There are many applications of this test. The most popularly used F-test is the hypothesis test of equality of two or more independent distributed populations, all having equal standard deviation. This is also known as ANOVA or Analysis of Variance technique. This is crucial to analyze this.

F-test can determine the major differences between three and more variable collected from an experimental research. It is performed to assess how widely an expected value within two independent groups is different from one another.

Some of the features of F-test are the following:

• The f-values are more than 0, which means they are nor negative
• It is a non-symmetric distribution
• The mean is 1
• There are two degrees of freedom. One for the numerator and another for the denominator.
• Different f-distributions are there. One for a pair

Chi-square statistical distribution is closely related to the continuous curve, called the chi-square distribution. It has just one parameter v. The probability function of this one depends on the degrees of freedom of v. With a change in v, ChiSquare’s probability function changes too. When there is an increase in the quantity of degree of freedom, the curve becomes symmetrical till the number attains higher values. If you are seeking best professional essay writing, research paper writing, and coursework writing service.

Conditions for the Ch-Square test are the following:

• The total number of frequencies say N should be large enough, greater than 50.
• The observations of the sample should be independent. This means that an individual item should not be included two times or more in a sample.
• If there are any constraints on the frequencies of the cell, it should be linear.
• There should not be any small cell frequency. If the frequencies are small then the x2 value will be overestimated. This shall reject the null hypothesis. Every theoretical frequency must be greater than 10 but not lesser than 5. If any of the theoretical frequencies is lesser than 5, x2 test cannot be applied. In such situations, the polishing technique is applied where the frequency is added where it is lesser than 5with either preceding or a succeeding frequency. This way the resulting sum will be greater than 5.
• This distribution must not be replaced by the proportions or relative frequencies.

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