Question

Please post a screenshot of excel file.

Application assignment: using Excel

Descriptive Statistics of Quantitative Data (measured on Ratio scale).

Use this file for submission, but use Excel to do your work and copy and paste in the appropriate places identified in this word file.

Note: The following Excel functions in answering Questions 1 and 2 below.

AVERAGE , AVEDEV, COUNT, CORREL, MIN, MAX, MDIAN, MODE, STDEV , STDEVP, STDEV.P, and STDEV.S

Q4.

1. Use the x data and define a new variable called U=X+10 by adding 10 to each of the x values.

Use the data for U and reuse Data Analysis descriptive Option to calculate the descriptive statistics of U.

Insert your answer here:

Descriptive for the U values:  

2. Compare the results for X with that of U and report the differences.

Insert your comparison answer here:

Answer 1

We used Excel to do some basic data analysis tasks to see whether it is a reasonable alternative to using a statistical package for the same tasks. We concluded that Excel is a poor choice for statistical analysis beyond textbook examples, the simplest descriptive statistics, or for more than a very few columns. The problems we encountered that led to this conclusion are in four general areas:

Missing values are handled inconsistently, and sometimes incorrectly.

Data organization differs according to analysis, forcing you to reorganize your data in many ways if you want to do many different analyses.

Many analyses can only be done on one column at a time, making it inconvenient to do the same analysis on many columns.

Output is poorly organized, sometimes inadequately labeled, and there is no record of how an analysis was accomplished.

Excel is convenient for data entry, and for quickly manipulating rows and columns prior to statistical analysis. However when you are ready to do the statistical analysis, we recommend the use of a statistical package such as SAS, SPSS, Stata, Systat or Minitab.

Introduction

Excel is probably the most commonly used spreadsheet for PCs. Newly purchased computers often arrive with Excel already loaded. It is easily used to do a variety of calculations, includes a collection of statistical functions, and a Data Analysis ToolPak. As a result, if you suddenly find you need to do some statistical analysis, you may turn to it as the obvious choice. We decided to do some testing to see how well Excel would serve as a Data Analysis application.

To present the results, we will use a small example. The data for this example is fictitious. It was chosen to have two categorical and two continuous variables, so that we could test a variety of basic statistical techniques. Since almost all real data sets have at least a few missing data points, and since the ability to deal with missing data correctly is one of the features that we take for granted in a statistical analysis package, we introduced two empty cells in the data:

Treatment

Outcome

X

Y

1

1

10.2

9.9

1

1

9.7

2

1

10.4

10.2

1

2

9.8

9.7

2

1

10.3

10.1

1

2

9.6

9.4

2

1

10.6

10.3

1

2

9.9

9.5

2

2

10.1

10

2

2

10.2