Datalogy Today

Hypothesis Testing We have methods to test our hypothesis and these methods can be categorized into two parts. Parametric Testing: This type of tests make assumptions about the Population parameters and the distributions that the data came from. These types of test  includes Student's T  tests  and ANOVA   tests , which assume data is from a normal distribution. Non- parametric Testing: Non - parametric tests  are used when there is  no  or few information available about the population parameters. Z Test: To find test statistics, we can use the below formula. Z test can be done if the below 3 points are satisfied. 1.      Sample size should be > 30. 2.      Population SD should be known. 3.      Variables should be continues. Steps for Z Test: 1.      State Null & Alternate Hypothesis. 2.      Find t...

Degrees Of Freedom: Degrees of freedom refers to the maximum number of logically independent values in a data sample which have the freedom to vary within. Example: If there is a sample of 3 values {5, x, 15} and the mean of all the values is 10. Now it is easy to say that the value of x would be 10 as the mean of these 3 values is 10. But if 2 values from this sample are not known, say {5, x, y} with same mean 10, then we are now cannot be sure about the exact values of x & y. It could be any values from (10, 15), (15, 10), (5, 20), (20, 5) or even (1, 24). So we cannot determine the exact value of these data x & y. These 2 values has a freedom to vary. But the third value do not have the freedom to change as it has to be some value so that the mean will not change. So this value depends upon all the other values. So the degrees of freedom of this sample data of size 3 is 2. Not only with size 3 sample, a sample with any size we can determine onl...

What is a Hypothesis Testing? The hypothesis is an assumption which is tested to determine whether the assumption is true or not. Hypothesis Testing is a process of testing the assumption. When we do the interpretation, we use statistical methods that provide a confidence or likelihood about the answers. These methods are called  statistical hypothesis testing , or significance tests . How to do Hypothesis Testing? In Hypothesis testing, the analysts take a random sample of a population and test it to prove the evidence on the acceptance. The results of this test allows us to explain (interpret) whether the assumption could be true or the assumption has been violated. When the assumption holds, we call it as Null Hypothesis. Ho When the assumption has been violated, we call it as Alternate Hypothesis. H1 or HA . But now we are confused that which should be considered as Null Hypothesis and which is our alternative. Null Hypothesis:...