What is a Null Hypothesis?

Difference between Null Hypothesis and Alternate Hypothesis

Hypothesis tests help identify differences between two or more items and whether the differences are statistically significant or not.

Null Hypothesis (Ho)

The null hypothesis is the statement that there is no statistically significant difference or relationship between variables.

Any differences that are observed are due to chance. It is a statement of "no effect" or "no difference."

Alternate Hypothesis (Ha)

The alternate hypothesis (Ha) is the opposite. The alternate hypothesis states that there is a statistically significant difference or relationship between variables.


The goal of a hypothesis test is to is to prove that they are not statistically the same at some level of confidence (usually 95%, 99%).

Tests can be either one sided or two sided depending on how the null hypothesis is stated.

Null Hypothesis
one sided test
Alternate Hypothesis
one sided test
 

Average1 <= Average2
Average1 >= Average2
Mean1 <= Mean2
Mean1 >= Mean2
Mean1 - Mean2 <= 0 
Mean1 - Mean2 >= 0

Average1 > Average2
Average1 < Average2 
Mean1 > Mean2 
Mean1 < Mean2
Mean1 - Mean2 > 0 
Mean1 - Mean2 < 0

statistics means never having to say you are certain

That's Why QI Macros Interprets the Results
of Statistical Tests for You

Variance1 <= Variance2
Variance1 > = Variance2
Variance1 > Variance2
Variance1 < Variance2
Null Hypothesis- two sided test Alternate Hypothesis - two sided test

Average1 = Average2
Mean1 = Mean2
Mean1 - Mean2 = 0 (no difference)

Average1 not = Average2
Mean1 not = Mean2 
Mean1 - Mean2 not = 0
Variance1 = Variance2 Variance1 not = Variance2

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Hypothesis testing

Type I and Type II Errors


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