key elementary statistical concepts .

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Analysis and Evaluation RESOURCES I PRIMT I HELP

Analysis

By itself, test data is rarely useful to decision-makers. It must be turned into information. A vital step towards producing useful information from raw test data is analysis . Analysis involves more than just re­ stating the data.

Analysis is the process of using various mathematical or graphical techniques to structure and interpret test data in order to identify patterns, comparisons, or cause/ effect.

Analysis involves asking several questions:

• Is the data reasonable?

• Has enough data been gathered?

• Is the quality o f the data sufficient?

The use of statistics is a key tool in the overall analysis process.

I s t he dat a reasonable?

This question reflects the comparison of the pre-test predictions with the actual test results to verify the test was run properly and the data falls within the expected range .

~ I Page4of 24 ~ Back liiii ) Next

TST102 Fundamentals of Test Evaluation

Lesson 19 – Analysis and Evaluation RESOURCES I PRIMT I HELP

Analysis

By itself, test data is rarely useful to decision-makers. It must be turned into information. A vital step towards producing useful information from raw test data is analysis . Analysis involves more than just re­ stating the data.

Analysis is the process of using various mathematical or graphical techniques to structure and interpret test data in order to identify patterns, comparisons, or cause/ effect.

Analysis involves asking several questions:

• Is the data reasonable?

• Has enough data been gathered?

• Is the quality o f the data sufficient?

The use of statistics is a key tool in the overall analysis process.

Has enough dat a been gat hered?

This question is also asked during the post-test conduct phase of the T&E process to see if the sample size of good data supports analysis at the desired confidence level.

~ I Page4of 24 ~ Back liiii ) Next

TST102 Fundamentals of Test Evaluation

Lesson 19 – Analysis and Evaluation RESOURCES I PRIMT I HELP

Analysis

By itself, test data is rarely useful to decision-makers. It must be turned into information. A vital step towards producing useful information from raw test data is analysis . Analysis involves more than just re­ stating the data.

Analysis is the process of using various mathematical or graphical techniques to structure and interpret test data in order to identify patterns, comparisons, or cause/ effect.

Analysis involves asking several questions:

• Is the data reasonable?

• Has enough data been gathered?

• Is the quality o f the data sufficient?

The use of statistics is a key tool in the overall analysis process.

Is the quality of the da ta s ufficient?

This question is also asked during the post-test conduct phase of the T&E process to verify that the data authentication process certifies the data as acceptable for analysis .

~ I Page4of 24 ~ Back liiii ) Next

TST102 Fundamentals of Test Evaluation

Lesson 19 – Analysis and Evaluation RESOURCES I PRIMT I HELP

Review of Some Basic Statistics Concepts

Statistics is the collection and interpretation of quantitative data and the use of mathematics to estimate population parameters. In testing, the analyses of sample data, using statistical techniques, looks for what happened, how well the test article performed vs. some criteria, and makes predictions about future performance. The use of statistics for test design and analysis requires extensive training , beyond the scope of this course . However, testers should nevertheless understand some key concepts and terms, which have been simplified and summarized below and in the following screens.

Basic statistics Concepts and Terms:

Descriptiv e statistics : describes data in formats such as bar charts, graphs, histograms, curves, and frequency distributions. Examples are means, modes, median, range, and standard deviation.

Inferential statistics : draws conclusions from sample data to estimate performance of the entire population.

….rl I Page S of 24 ~ Back Next

TST102 Fundamentals of Test Evaluation

Lesson 19 – Analysis and Evaluation RESOURCES I PRIMT I HELP

Review of Some Basic St atistics Concepts

Sta tis tics is the collec tion and interpretation of quantitative data and the use of mathematics to estimate population parameters. In testing, the analyses of sample data, using statistical techniques, looks for what happened, how well the test article performed vs. some criteria, and makes predictions about future performance. The use of statistics for test design and analysis requires extensive training , beyond the scope of this course . However, testers should nevertheless understand some key concepts and terms, which have been simplified and summarized below and in the following screens.

Basic statistics ConcJ ———————–… Long Description

Descriptiv e statistics : tograms, curves, and frequency distributions. A large circle with the word population surrounds a deviation.

smaller circle with word sample.

Inferential statistics : ~m!”‘!!!l’l’l’l!’lml~i!”‘l~lll'”~'”!lll!”!lll~~l”!mmlft!-,m!l’l’lmfhce of the en tire population.

….rl I PageSof 24 ~ Back Next

TST102 Fundamentals of Test Evaluation

Lesson 19 – Analysis and Evaluation RESOURCES I PRIMT I HELP

Review of Some Basic Statistics Concepts

Statistics is the collection and interpretation of quantitative data and the use of mathematics to estimate population parameters. In testing, the analyses of sample data, using statistical techniques, looks for what happened, how well the test article performed vs. some criteria, and makes predictions about future performance. The use of statistics for test design and analysis requires extensive training , beyond the scope of this course . However, testers should nevertheless understand some key concepts and terms, which have been simplified and summarized below and in the following screens.

Basic statistics Concept~ Extensive Training

Descriptive statistics: de frequency dis tribu tions. Ex.

Refreshers on basic statistic concep ts are available as a Con tinuous Learning Module (CLE

istograms, curves, and rd deviation.

Inferential statistics: dra 035), accessible via the DAU Continuous Learning Center as well as other sources. See References ance of the entire

population. for details .

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