Question4: The times for untrained rats to run a standard maze has a normal distribution where the times are measured in seconds. The researcher hopes to show that training improves the times. A sample of 9 rats were selected and the time to run a standard maze before and after training were measured in seconds and shown below. Does the data support the researcher’s hypothesis? Conduct a hypothesis test at 5% significant level (specify 4 steps). ## Experimental Data: Weight MeasurementsThe table below shows the weight measurements of rats before and after a certain treatment. Each rat's weight is recorded in units consistent throughout the study.| Rat | Before | After ||-----|--------|-------|| 1 | 60 | 60 || 2 | 65 | 60 || 3 | 70 | 64 || 4 | 58 | 59 || 5 | 74 | 65 || 6 | 63 | 62 || 7 | 72 | 68 || 8 | 66 | 64 || 9 | 67 | 62 |### Analysis- **Categories:** - **Before:** This column lists the initial weight of each rat before the treatment was applied. - **After:** This column shows the weight of each rat after the treatment.### Observations- Rat 1 maintained the same weight before and after the treatment.- Rat 2, 6, and 9 showed a decrease in weight after the treatment.- The other rats exhibited varied decreases in weight, with Rat 5 showing the most significant change from 74 to 65.This data can be useful in understanding the effect of the specified treatment on the weight of the rats. Further statistical analysis can be performed to determine the significance of the changes observed.

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Description: Question4: The times for untrained rats to run a standard maze has a normal distribution where the times are measured in seconds. The researcher hopes to show that training improves the times. A sample of 9 rats were selected and the time to run a st

Given, Rat Before After 1 60 60 2 65 60 3 70 64 4 58 59…

Answered: Question4: The times for untrained rats…

MATLAB: An Introduction with Applications

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ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

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Question4: The times for untrained rats to run a standard maze has a normal distribution where the times are measured in seconds. The researcher hopes to show that training improves the times. A sample of 9 rats were selected and the time to run a standard maze before and after training were measured in seconds and shown below. Does the data support the researcher’s hypothesis? Conduct a hypothesis test at 5% significant level (specify 4 steps).

## Experimental Data: Weight Measurements

The table below shows the weight measurements of rats before and after a certain treatment. Each rat's weight is recorded in units consistent throughout the study.

| Rat | Before | After |
|-----|--------|-------|
| 1 | 60 | 60 |
| 2 | 65 | 60 |
| 3 | 70 | 64 |
| 4 | 58 | 59 |
| 5 | 74 | 65 |
| 6 | 63 | 62 |
| 7 | 72 | 68 |
| 8 | 66 | 64 |
| 9 | 67 | 62 |

### Analysis

- **Categories:**
- **Before:** This column lists the initial weight of each rat before the treatment was applied.
- **After:** This column shows the weight of each rat after the treatment.

### Observations

- Rat 1 maintained the same weight before and after the treatment.
- Rat 2, 6, and 9 showed a decrease in weight after the treatment.
- The other rats exhibited varied decreases in weight, with Rat 5 showing the most significant change from 74 to 65.

This data can be useful in understanding the effect of the specified treatment on the weight of the rats. Further statistical analysis can be performed to determine the significance of the changes observed.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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