For this discussion you will need to come up with twenty different data points and enter them into the first column in Excel. The data points can be any numbers you want as long as there are twenty of them. You will then use the descriptive statistics option in Excel, which is explained in your text, you should get an output similar to figure 1.2. This output should contain the mean, standard error, median, mode, standard deviation, sample variance, kurtosis, skewness, range, minimum, maximum, sum, count. Be sure to begin your discussion by reporting your results for each of these values. Based on this output which single value best describes this set of data and why? If you could pick three of these values instead of only one, which three would you choose and why? It is important to note that the answers to these questions may be different for each of you as you are all using unique sets of data.

To complete this task, you will need to follow the steps below:

Step 1: Open Excel and enter your twenty data points in the first column, starting from row 1. Let's say you choose the numbers 1, 2, 3, ..., 20.

Step 2: Once you have entered the data points, select the range of cells containing your data. In this case, select cells A1 to A20.

Step 3: Go to the "Data" tab in Excel's ribbon and locate the "Data Analysis" option. If you don't see this option, you may need to enable the Data Analysis Toolpak. To enable it, go to "File" > "Options" > "Add-Ins" > "Excel Add-ins" > Check "Analysis ToolPak" > Click "OK".

Step 4: Click on "Data Analysis" and then select "Descriptive Statistics" from the list of analysis tools. Click "OK".

Step 5: In the Descriptive Statistics dialog box, select the input range (A1 to A20), select the "Summary statistics" option, and choose an output range where you want the results to be displayed. For example, you can select B1 as the upper-left cell of the output range.

Step 6: Click "OK" to generate the descriptive statistics output.

Now, let's discuss the results and answer the given questions:

1. Mean: The mean represents the average value of the dataset. It is calculated by summing up all the values and dividing by the number of data points. The mean of your dataset can be found in the output.

2. Standard Error: The standard error measures the variability or uncertainty in the mean estimation. It indicates how accurately the mean represents the population. The standard error can be found in the output.

3. Median: The median is the middle value of the dataset when it is arranged in ascending or descending order. If there is an even number of values, it is the average of the two middle values. The median of your dataset can be found in the output.

4. Mode: The mode represents the most frequently occurring value in the dataset. The mode of your dataset can be found in the output.

5. Standard Deviation: The standard deviation measures the dispersion or spread of the dataset around the mean. It provides an understanding of how the individual data points vary from the mean. The standard deviation of your dataset can be found in the output.

6. Sample Variance: The sample variance quantifies the average squared deviation of each data point from the mean. It is directly related to the standard deviation. The sample variance of your dataset can be found in the output.

7. Kurtosis: Kurtosis measures the heaviness or lightness of the tails of the distribution compared to a normal distribution. Positive kurtosis indicates heavier tails, while negative kurtosis suggests lighter tails. The kurtosis of your dataset can be found in the output.

8. Skewness: Skewness measures the asymmetry of the distribution. Positive skewness indicates a longer or fatter tail on the right side of the distribution, while negative skewness suggests a longer or fatter tail on the left side. The skewness of your dataset can be found in the output.

9. Range: The range represents the difference between the maximum and minimum values of the dataset. It indicates the spread of data from the lowest to the highest value. The range of your dataset can be found in the output.

10. Minimum: The minimum is the smallest value in the dataset. It represents the floor or lower boundary of the data range. The minimum of your dataset can be found in the output.

11. Maximum: The maximum is the largest value in the dataset. It represents the ceiling or upper boundary of the data range. The maximum of your dataset can be found in the output.

12. Sum: The sum represents the total of all the data points in the dataset. It is obtained by adding up all the values. The sum of your dataset can be found in the output.

13. Count: The count represents the number of data points in the dataset. It is simply the total number of values. The count of your dataset can be found in the output.

Based on the output of these descriptive statistics for your unique set of data, you can assess which single value or combination of values best describe the dataset. The choice may vary depending on the characteristics of your data.

If you were to pick three values, you could consider the following possibilities:

1. Mean: The mean provides an overall measure that takes into account all the data points. It represents the central tendency of the dataset.

2. Standard Deviation: The standard deviation gives an indication of the dispersion or variability in the data points relative to the mean. It provides insights into the spread or scatter of the dataset.

3. Skewness: Skewness can help identify any asymmetry in the data distribution. It provides information about the tail behavior and departure from a symmetric distribution.

However, the specific choice of three values may vary depending on the nature and objectives of your analysis.