## Do you ever reject the alternative hypothesis?

After you perform a hypothesis test, there are only two possible outcomes. When your p-value is less than or equal to your significance level, you reject the null hypothesis. The data favors the alternative hypothesis. When your p-value is greater than your significance level, you fail to reject the null hypothesis.

## What is the null hypothesis for a paired t-test?

The null hypothesis is that the mean difference between paired observations is zero. When the mean difference is zero, the means of the two groups must also be equal. Because of the paired design of the data, the null hypothesis of a paired t–test is usually expressed in terms of the mean difference.

**Can the hypothesis be a question?**

Before you make a hypothesis, you have to clearly identify the question you are interested in studying. A hypothesis is a statement, not a question. Your hypothesis is not the scientific question in your project. The hypothesis is an educated, testable prediction about what will happen.

**How do you use a t-test to test a hypothesis?**

Computing scores for a single-sample test

- Take the following input:
- Extract the number of samples (n).
- Calculate the mean of the sample data.
- Calculate the standard deviation (s) of the sample data.
- Calculate t and degrees of freedom (df):
- Extract probability P from distribution table T by using t and df.

### What is the null hypothesis for a two sample t test?

The default null hypothesis for a 2-sample t-test is that the two groups are equal. You can see in the equation that when the two groups are equal, the difference (and the entire ratio) also equals zero.

### How do you turn a question into a statement?

In a standard English yes-or-no question, the verb precedes the subject, often a helping verb like “is,” “must” or “can.” If the question is not yes-or-no, it begins with a question word, like “who,” “what,” “when” or “where.” To turn a question into a statement, remove the question word and put the sentence into …

**What is the difference between chi square and t-test?**

A t-test tests a null hypothesis about two means; most often, it tests the hypothesis that two means are equal, or that the difference between them is zero. A chi-square test tests a null hypothesis about the relationship between two variables.

**Why do we use t-test instead of Z test?**

Z-tests are statistical calculations that can be used to compare population means to a sample’s. T-tests are calculations used to test a hypothesis, but they are most useful when we need to determine if there is a statistically significant difference between two independent sample groups.

## What is p value in Z test?

The first way to find the p-value is to use the z-table. In the z-table, the left column will show values to the tenths place, while the top row will show values to the hundredths place. If we have a z-score of -1.304, we need to round this to the hundredths place, or -1.30.