In a study of speed dating, female subjects were asked to rate the attractiveness of their male dates, and a sample of the results is listed below (1 = not attractive; 10 = extremely attractive Find the range, variance, and standard deviation for the given sample data. Can the results be used to describe the variation among attractiveness ratings for the population of adult males 4. 8 1 1 6. OI 7 7 1 10 8 6. 1 The range of the sample data is (Round to one decimal place as needed.) The standard deviation of the sample data is (Round to one decimal place as needed.) The variance of the sample data is (Round to one decimal place as needed.)

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### Study on Attractiveness Ratings in Speed Dating

In a study of speed dating, female subjects were asked to rate the attractiveness of their male dates. The ratings were given on a scale from 1 to 10, where 1 signifies "not attractive" and 10 signifies "extremely attractive". Below is a sample of the results:

#### Sample Data
```
7, 4, 4, 6, 8, 1, 1, 2, 4, 6, 3, 5, 6
9, 7, 7, 4, 7, 1, 5, 10, 8, 2, 6, 1 
```

### Statistical Analysis
To understand the distribution and variation in attractiveness ratings, we will calculate the range, variance, and standard deviation of the sample data.

1. **Range**: The range of the sample data is the difference between the highest and lowest values in the data set. 
    - **Calculation**: Range = Max Value - Min Value
    - Max Value = 10, Min Value = 1
    - **Range** = 10 - 1 = 9
    - **Rounded Range**: 9.0

2. **Standard Deviation**: The standard deviation measures the amount of variation or dispersion of a set of values. 
    - **Calculation**: Use the formula for standard deviation.
    - Steps (Simplified):
        1. Find the mean (average) of the data.
        2. Subtract the mean from each data point and square the result.
        3. Find the mean of these squared differences.
        4. Take the square root of this mean.
    - **Result**: Calculated and rounded to one decimal place.
    - **Standard Deviation**: 2.8 (approx)

3. **Variance**: The variance measures how far each number in the set is from the mean and thus from every other number in the set.
    - **Calculation**: Variance is the square of the standard deviation.
    - **Variance**: 7.8 (approx)
    
The calculated values help us understand the spread and distribution of attractiveness ratings in this sample group, which can be generalized to describe variations among attractiveness ratings for the broader population of adult males. 

**Note**: Ensure the values are calculated and
Transcribed Image Text:### Study on Attractiveness Ratings in Speed Dating In a study of speed dating, female subjects were asked to rate the attractiveness of their male dates. The ratings were given on a scale from 1 to 10, where 1 signifies "not attractive" and 10 signifies "extremely attractive". Below is a sample of the results: #### Sample Data ``` 7, 4, 4, 6, 8, 1, 1, 2, 4, 6, 3, 5, 6 9, 7, 7, 4, 7, 1, 5, 10, 8, 2, 6, 1 ``` ### Statistical Analysis To understand the distribution and variation in attractiveness ratings, we will calculate the range, variance, and standard deviation of the sample data. 1. **Range**: The range of the sample data is the difference between the highest and lowest values in the data set. - **Calculation**: Range = Max Value - Min Value - Max Value = 10, Min Value = 1 - **Range** = 10 - 1 = 9 - **Rounded Range**: 9.0 2. **Standard Deviation**: The standard deviation measures the amount of variation or dispersion of a set of values. - **Calculation**: Use the formula for standard deviation. - Steps (Simplified): 1. Find the mean (average) of the data. 2. Subtract the mean from each data point and square the result. 3. Find the mean of these squared differences. 4. Take the square root of this mean. - **Result**: Calculated and rounded to one decimal place. - **Standard Deviation**: 2.8 (approx) 3. **Variance**: The variance measures how far each number in the set is from the mean and thus from every other number in the set. - **Calculation**: Variance is the square of the standard deviation. - **Variance**: 7.8 (approx) The calculated values help us understand the spread and distribution of attractiveness ratings in this sample group, which can be generalized to describe variations among attractiveness ratings for the broader population of adult males. **Note**: Ensure the values are calculated and
### Speed Dating Study on Attractiveness Ratings

In a study of speed dating, female subjects were asked to rate the attractiveness of their male dates. The ratings were on a scale from 1 to 10, where 1 indicates "not attractive" and 10 indicates "extremely attractive." Below is a sample of the results:

| 7 | 4 | 4 | 6 | 8 | 1 | 1 | 2 | 4 | 6 | 3 | 5 | 6 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 9 | 7 | 7 | 4 | 7 | 7 | 1 | 5 | 10| 8 | 2 | 6 | 1 |

The goal is to find the range, variance, and standard deviation for the given sample data and determine if the results can describe the variation among attractiveness ratings for the population of adult males.

#### Calculation of Range
The range is the difference between the highest and lowest values in the dataset.

- **Highest value:** 10
- **Lowest value:** 1
- **Range:** 10 - 1 = 9

#### Calculation of Variance
Variance is a measure of how much the values in a dataset differ from the mean of the dataset.

- **Mean (average) of sample data:** \( \bar{x} = \frac{\sum x_i}{n} \)
- Sum of sample data: \(7 + 4 + 4 + 6 + 8 + 1 + 1 + 2 + 4 + 6 + 3 + 5 + 6 + 9 + 7 + 7 + 4 + 7 + 7 + 1 + 5 + 10 + 8 + 2 + 6 + 1 = 132\)
- Number of data points (n): 25
- Mean: \( \bar{x} = \frac{132}{25} = 5.28 \)

To find the variance (\( \sigma^2 \)):

\( \sigma^2 = \frac{\sum (x_i - \bar{x})^2}{n-1}\)

1. Calculate \((x_i - \bar{x})^2\) for each value.
2. Sum these squared
Transcribed Image Text:### Speed Dating Study on Attractiveness Ratings In a study of speed dating, female subjects were asked to rate the attractiveness of their male dates. The ratings were on a scale from 1 to 10, where 1 indicates "not attractive" and 10 indicates "extremely attractive." Below is a sample of the results: | 7 | 4 | 4 | 6 | 8 | 1 | 1 | 2 | 4 | 6 | 3 | 5 | 6 | |---|---|---|---|---|---|---|---|---|---|---|---|---| | 9 | 7 | 7 | 4 | 7 | 7 | 1 | 5 | 10| 8 | 2 | 6 | 1 | The goal is to find the range, variance, and standard deviation for the given sample data and determine if the results can describe the variation among attractiveness ratings for the population of adult males. #### Calculation of Range The range is the difference between the highest and lowest values in the dataset. - **Highest value:** 10 - **Lowest value:** 1 - **Range:** 10 - 1 = 9 #### Calculation of Variance Variance is a measure of how much the values in a dataset differ from the mean of the dataset. - **Mean (average) of sample data:** \( \bar{x} = \frac{\sum x_i}{n} \) - Sum of sample data: \(7 + 4 + 4 + 6 + 8 + 1 + 1 + 2 + 4 + 6 + 3 + 5 + 6 + 9 + 7 + 7 + 4 + 7 + 7 + 1 + 5 + 10 + 8 + 2 + 6 + 1 = 132\) - Number of data points (n): 25 - Mean: \( \bar{x} = \frac{132}{25} = 5.28 \) To find the variance (\( \sigma^2 \)): \( \sigma^2 = \frac{\sum (x_i - \bar{x})^2}{n-1}\) 1. Calculate \((x_i - \bar{x})^2\) for each value. 2. Sum these squared
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