Use Sheet 2 of the Excel file to answer the following questions. A school administrator believes that the mean class GPAS for a given course are higher than the preferred mean of 2.75 at a significance level of 0.05, and checks a randomly chosen sampie of 50 classes. Create a histogram, and calculate r, the t-statistic, and the p-value. From the histogram, can normality be assumed? Pick Yes I = Ex: 1.234 No t%3D Since the p-value is Pick than the significance level 0.05, the null hypothesis Pick
Use Sheet 2 of the Excel file to answer the following questions. A school administrator believes that the mean class GPAS for a given course are higher than the preferred mean of 2.75 at a significance level of 0.05, and checks a randomly chosen sampie of 50 classes. Create a histogram, and calculate r, the t-statistic, and the p-value. From the histogram, can normality be assumed? Pick Yes I = Ex: 1.234 No t%3D Since the p-value is Pick than the significance level 0.05, the null hypothesis Pick
Use Sheet 2 of the Excel file to answer the following questions. A school administrator believes that the mean class GPAS for a given course are higher than the preferred mean of 2.75 at a significance level of 0.05, and checks a randomly chosen sampie of 50 classes. Create a histogram, and calculate r, the t-statistic, and the p-value. From the histogram, can normality be assumed? Pick Yes I = Ex: 1.234 No t%3D Since the p-value is Pick than the significance level 0.05, the null hypothesis Pick
Hi,
Please answer all parts.
Last 3 parts, the options are:
P Value :
greater than
Less than
Null hypothesis:
Fails to be rejected
Is rejected
Mean GPA:
Sufficient
Insufficient
Transcribed Image Text:**Challenge Activity: 5.2.2: Excel: Hypothesis Test for a Population Mean**
### Instructions:
Click [this link](#) to download the spreadsheet for use in this activity.
**Jump to level 1**
---
**Instructions:**
Use Sheet 2 of the Excel file to answer the following questions:
---
*A school administrator believes that the mean class GPAs for a given course are higher than the preferred mean of 2.75 at a significance level of 0.05, and checks a randomly chosen sample of 50 classes. Create a histogram and calculate the sample mean (\(\bar{x}\)), the t-statistic, and the p-value.*
---
1. **From the histogram, can normality be assumed?**
- **Options:**
- Yes
- No
2. **Calculate the sample mean (\(\bar{x}\)):**
\(\bar{x} =\) (Provide the calculated value)
3. **Calculate the t-statistic:**
\(t =\) (Provide the calculated value)
4. **Calculate the p-value:**
\(p =\) (Provide the calculated value)
5. **Decision Making:**
Since the \(p\)-value is (Select \(>\) or \(<\)) than the significance level 0.05, the null hypothesis (Select "can be rejected" or "cannot be rejected").
(Select "Sufficient" or "Insufficient") evidence exists that the mean GPA is greater than 2.75.
---
***Interface:***
Below these instructions, there are input boxes and selection options for users to enter data and make selections. Options include buttons such as "Check" and "Next" to progress through the activity.
Transcribed Image Text:**Title: Analyzing Frequency Distribution with Histogram and Cumulative Percentage Line**
**Introduction:**
In this session, we will review the frequency distribution of a dataset labeled "Field1" and understand its behavior through graphical representation. This will help you gain insights into the concentration and spread of the data points. The dataset is visualized using a histogram combined with a cumulative percentage line.
**Dataset Overview:**
The data values in "Field1" are listed from cells A1 to A64. These values range from 2.24 to 3.14. Here is the complete list:
- 3.09
- 2.73
- 2.58
- 2.48
- 2.77
- ...
- 2.84
- 3.10
- 2.62
- 2.77
**Frequency Distribution Analysis:**
1. **Histogram:**
- The histogram plots the frequency of data values in specified intervals (bins). The intervals used are:
- [2.64, 2.74)
- [2.74, 2.84)
- [2.84, 2.94)
- [2.94, 3.04)
- [2.04, 2.64)
- [2.34, 2.44)
- [2.44, 2.54)
- [3.04, 3.14)
- The x-axis represents these intervals for "Field1".
- The y-axis on the left represents the frequency, showing how many values fall within each bin.
- The height of the bars indicates the number of data points within each interval.
2. **Cumulative Percentage Line:**
- The orange line represents the cumulative percentage of data points up to each interval.
- The y-axis on the right indicates the cumulative percentage.
- It helps in understanding the proportion of data points below a certain threshold.
**Key Observations:**
- The first bin [2.64, 2.74) has the highest frequency of data points (12).
- Subsequent bins show a declining trend in frequency.
- The cumulative percentage line starts at the first bin and reaches 100% by the end of the last bin, indicating all data points are accounted for.
**Conclusion:**
Understanding frequency distribution through histograms and cumulative percentage lines enables better
Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...
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 to download the spreadsheet for use in this activity.
**Jump to level 1**
---
**Instructions:**
Use Sheet 2 of the Excel file to answer the following questions:
---
*A school administrator believes that the mean class GPAs for a given course are higher than the preferred mean of 2.75 at a significance level of 0.05, and checks a randomly chosen sample of 50 classes. Create a histogram and calculate the sample mean (\(\bar{x}\)), the t-statistic, and the p-value.*
---
1. **From the histogram, can normality be assumed?**
- **Options:**
- Yes
- No
2. **Calculate the sample mean (\(\bar{x}\)):**
\(\bar{x} =\) (Provide the calculated value)
3. **Calculate the t-statistic:**
\(t =\) (Provide the calculated value)
4. **Calculate the p-value:**
\(p =\) (Provide the calculated value)
5. **Decision Making:**
Since the \(p\)-value is (Select \(>\) or \(<\)) than the significance level 0.05, the null hypothesis (Select "can be rejected" or "cannot be rejected").
(Select "Sufficient" or "Insufficient") evidence exists that the mean GPA is greater than 2.75.
---
***Interface:***
Below these instructions, there are input boxes and selection options for users to enter data and make selections. Options include buttons such as "Check" and "Next" to progress through the activity.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F52bd3cfe-3c9b-40ce-8732-3b0b81ba9280%2F9a9f5af4-b233-42af-b314-7573d3cd6316%2F7vbpn1_processed.jpeg&w=3840&q=75)
