WEEK 9 Discussion
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WEEK9 :
Discussion Question
Using the Excel Sheet and descriptive statistics page; you will write up your analysis for the 20 participants.
This week, you learned about the statistical software applications used to analyze data for research analysis. For this week's discussion, you will use Excel sheet provide to run descriptive statistics, create graphs and respond to the following:
· How could you use Excel descriptive statistics for data analysis research?
· What are your plans for learning more about Excel and how will the information you learned about this software be of benefit in your future analysis of research data?
Refer to this week’s readings and video tutorials before starting this two part discussion question assignment. You will also have access to the Assignment Resources Step-by-Step Guide, accessed through the Assignment Resources Icon located to the right of the grading criteria above.
Step 1: Entering Data
Open a blank worksheet in the Excel program
You will now use Excel to view a sample dataset
Dataset Options
In many cases, researchers may have the data from their study in another software package like Microsoft Excel. However, if the data is not available in a software spreadsheet you can manually enter the data. Option 2: Manual Data Entry
In the Worksheet window, type “Age” in C1. Enter the numbers as shown in the dataset below. Enter the remaining data as shown below (set up your column labels i.e., variable). The measure reflects math anxiety and the study variables (cringe, uneasy, afraid, worried, understand) the math anxiety range is from 1–5 with low being the least and 5 the highest.
Age |
Cringe |
Uneasy |
Afraid |
Worried |
Understand |
28 |
5 |
3 |
4 |
4 |
3 |
34 |
2 |
5 |
3 |
2 |
1 |
25 |
4 |
4 |
4 |
2 |
5 |
56 |
3 |
4 |
3 |
1 |
2 |
23 |
5 |
4 |
3 |
3 |
4 |
29 |
1 |
5 |
3 |
2 |
3 |
30 |
3 |
3 |
5 |
2 |
5 |
59 |
2 |
5 |
5 |
1 |
2 |
45 |
4 |
2 |
5 |
3 |
3 |
38 |
1 |
2 |
4 |
1 |
1 |
33 |
3 |
2 |
4 |
3 |
2 |
47 |
4 |
2 |
3 |
4 |
5 |
24 |
1 |
5 |
3 |
4 |
4 |
29 |
5 |
4 |
2 |
1 |
3 |
53 |
3 |
1 |
5 |
2 |
1 |
48 |
4 |
4 |
1 |
5 |
3 |
27 |
2 |
5 |
4 |
3 |
4 |
34 |
4 |
4 |
3 |
2 |
5 |
26 |
4 |
5 |
2 |
3 |
2 |
36 |
5 |
5 |
5 |
4 |
3 |
Step 2: Click on Excel tab for Add Ins; if you do not see statistics; you will need to open the file option; click on Add ins; click on ok; a box will open which will allow you to choose Statistics package; place a check mark in the box and click ok. How to Run Descriptive Statistics
Now that your data is in Excel, you will look at the descriptive statistics for this dataset. Select the data in all the columns except the top that has words for the columns; however you have the file already completed and a picture of the descriptive statistics..See end of page for a copy of the excel sheet and descriptive statistics output.
Discussion Question Part 1
How could you use Excel descriptive statistics for data analysis research? Write about your experience running descriptive statistics. Use the results in the Session Window to support your response. Then add to your discussion with the information you learn writing up your analysis.
Step 3: Excel and Graphs
You will now look at graphing. Select insert graph located at the top of the sheet; highlight the data you want to use for a chart; select the type of chart; select ok. Try using the histogram feature for one of the variables and select "Ok". You can create other Histogram graphs by choosing different variables. You can also choose from the other ten graph choices shown on the insert chart function.
Discussion Question Part 2
What are your plans for learning more about Excel and how will the information you learned about this software be of benefit in your future analysis of research data? Copy and paste your graph(s) in a Word document and attach to your discussion response.
The task of descriptive statistics is to reduce hundreds of sample values using mathematical tools to several summary indicators that give an idea of the sample. These statistical indicators are: mode, variance, average, standard deviation, median and so on. For example, there is a description of a set of numeric data using certain indicators. These indicators will allow to draw certain statistical conclusions about the distribution from which the sample was taken. For instance, if there is a sample of pipe thickness values that are manufactured with the certain equipment, then based on the analysis of this sample one will be able, with some certain probability, to conclude on the state of the manufacturing process.
Analyzing the sample, which includes the age and emotions experienced by selected people using descriptive statistics, one can draw the following conclusions. The average age is 36.63 years (Avarage), while the youngest interviewed person is 23, and the oldest is 59. One can also confidently say that a half of these people are under 34 (Median), and half – are older. The most frequent age of respondents is 34 years (Mode). Of all the emotions listed, a high level can be given to “Uneasy”, as more than half of the respondents characterize it as "5" (Mode), and the lowest level of emotion has "Worried", as more than a half of the respondents rate it as "2" (Mode).
Graphical display of data makes the analysis of the received information easier. Thus, fig. 1 allows to draw the conclusions, mentioned earlier (about age, level of a certain emotion), however, with an increase in the sample, this analysis will be more difficult.
01234562834255623293059453833472429534827342636Level (from 1 to 5)Age, yearsCringeUneasyAfraidWorriedUndestand
Figure 1
Moreover, even the use of the graphs does not abolish the time for counting. Automated calculations in Excel allow to dramatically reduce the time and simplify the analysis of a large data sample, which makes this program very convenient and is an essential argument for studying its further capabilities.