Hello! Good to see your interest in learning statistics.

Today, we are going to go through the steps of performing the Walf-Wolfowitz run test. Remember, the easiest way to understand hypothesis testing is to solve an example. So intead of boring you with explanations, we would solve an example together. I would be explaining as we solve.

Wald-Wolfowitz Test (also called Wald-Wolfowitz run test) is a non-parametric hypothesis test used to test the randomness of a two-valued data sequence. It tests to see if the sequence are mutually independent.

The three formulas for the Wald-Wolfowitz run test are given below:

where the mean is given by the formula

and the variance is given by the formula

Let's now solve an example!

There are two IVM(Innoson Vehicle Manufacturers) buses, one with 48 passengers, and another with 38 passengers.

Let X and Y denote the number of miles travelled per day for the 48-passenger and 38-passenger buses respectively. Innoson would like to test the equality of the two distributions.

That is, if:

H

The company observed the following data on a random sample of n1 = 10 buses carrying 48 passengers and n2 = 11 buses carying 38 passengers.

X: 104 253 300 308 315 323 331 396 414 452

Y: 184 196 197 248 260 279 355 386 393 432 450

Using normal approximation to R, conduct a Wald-Wolfowitz test at 0.05 level of significance

We would solve this problem step by step.

H

H

Rejection criteria: Reject the null hypothesis if

104 184 196 197 248 253 260 279 300 308 315 331 355 386 393 394 414 432 450 452

Number of runs R = 9

n1 = 10

n2 = 11

We calculate the mean using the formular and we have the results below

We calculation the variance using the calculation steps below

We calculate the value of Z following the formula below:

We fail to reject the null hypothesis ast the 0.05 level because the P value is greater thatn 0.05. This means that there is not sufficient evidence at 0.05 level to conclude that the two distribution functions are not equal.

Thanks for your effort in learning statistics. If you have any challenge, let me know in the comment box below.

Today, we are going to go through the steps of performing the Walf-Wolfowitz run test. Remember, the easiest way to understand hypothesis testing is to solve an example. So intead of boring you with explanations, we would solve an example together. I would be explaining as we solve.

**Content**- Step 1: State the null and alternate hypothesis
- Step 2: Merge and sort the values in order
- Step 3: Calculate the Mean
- Step 4: Calculate the Variance
- Step 5: Calculate Z statistic
- Step 6: Draw your conclusion

### What is Wald-Wolfowitz Test?

Wald-Wolfowitz Test (also called Wald-Wolfowitz run test) is a non-parametric hypothesis test used to test the randomness of a two-valued data sequence. It tests to see if the sequence are mutually independent.

### Formula for Wald-Wolfowitz Test

The three formulas for the Wald-Wolfowitz run test are given below:

where the mean is given by the formula

and the variance is given by the formula

**Note**: Variance is the square of the standard deviation. So we calculated variance. To get the standard deviation, we must take the square root of the variance.Let's now solve an example!

### Example 1

There are two IVM(Innoson Vehicle Manufacturers) buses, one with 48 passengers, and another with 38 passengers.

Let X and Y denote the number of miles travelled per day for the 48-passenger and 38-passenger buses respectively. Innoson would like to test the equality of the two distributions.

That is, if:

H

_{0}: F(z) = G(z)The company observed the following data on a random sample of n1 = 10 buses carrying 48 passengers and n2 = 11 buses carying 38 passengers.

X: 104 253 300 308 315 323 331 396 414 452

Y: 184 196 197 248 260 279 355 386 393 432 450

Using normal approximation to R, conduct a Wald-Wolfowitz test at 0.05 level of significance

### Solution

We would solve this problem step by step.

**Step 1:** State the null and the alternate hypothesis and rejection criteria

H

_{0}: F(z) = G(z)H

_{1}: F(z) = G(z)Rejection criteria: Reject the null hypothesis if

### Step 2: Merge the two lists and sort in ascending order

104 184 196 197 248 253 260 279 300 308 315 331 355 386 393 394 414 432 450 452

### Step 3: Count the number of runs: R, n

### Step 3: Count the number of runs: R, n_{1} and n_{2}

Number of runs R = 9

n1 = 10

n2 = 11

### Step 4: Calculate the mean

We calculate the mean using the formular and we have the results below

### Step 5: Calculate the variance

We calculation the variance using the calculation steps below

### Step 6: Calculate Z

We calculate the value of Z following the formula below:

**Note**: Used 9.5 intead of 9 because we applied half-unit correction for continuity### Step 7: Draw your conclusion

We fail to reject the null hypothesis ast the 0.05 level because the P value is greater thatn 0.05. This means that there is not sufficient evidence at 0.05 level to conclude that the two distribution functions are not equal.

Thanks for your effort in learning statistics. If you have any challenge, let me know in the comment box below.