Professional Development Presentation- Descriptive Statistics

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Grand Canyon University *

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Feb 20, 2024

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Professional Development : Descriptive Statistics Professional Development : Descriptive Statistics Chelsea Badey Grand Canyon University SPD 556 Chelsea Badey Grand Canyon University SPD 556

Descriptive Statistics Descriptive Statistics  Summarize the sample studied without making inferences based on probability theory.  Can be used to describe a single or multiple variables.  Summarize the sample studied without making inferences based on probability theory.  Can be used to describe a single or multiple variables.

Reliability vs. Validity Reliability vs. Validity  Reliability is the degree to which an assessment tool produces stable and consistent results.  Validity refers to how well a test measures what it is supposed to measure.  Reliability is the degree to which an assessment tool produces stable and consistent results.  Validity refers to how well a test measures what it is supposed to measure.

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Test Bias Test Bias  Test bias is the differential validity of test scores. Bias is a systematic error in the process of measurement that influences scores for identified groups.  These tests are taken by students in a specific group that are disadvantaged.  Produce negative results and an invalid evaluation.  Test bias is the differential validity of test scores. Bias is a systematic error in the process of measurement that influences scores for identified groups.  These tests are taken by students in a specific group that are disadvantaged.  Produce negative results and an invalid evaluation.

Bell Curve Bell Curve  A bell curve is a graph that shows the typical distribution of information, and the shape is similar to a bell.  Shows percentages of students who test.  Shows progress or lack thereof.  A bell curve is a graph that shows the typical distribution of information, and the shape is similar to a bell.  Shows percentages of students who test.  Shows progress or lack thereof.

Mean Mean THE MEAN IS THE AVERAGE OF A SET OF NUMBERS, OR THE 50 TH PERCENTILE. THE MEAN IS THE AVERAGE OF A SET OF NUMBERS, OR THE 50 TH PERCENTILE.

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Standard Deviation and Standard Scores Standard Deviation and Standard Scores  Measurements of the bell curve.  Measure distance between scores  0 standard deviation is also the mean  Measure student growth  Standard scores changed to create the standard deviation  Graph shows as an example  Measurements of the bell curve.  Measure distance between scores  0 standard deviation is also the mean  Measure student growth  Standard scores changed to create the standard deviation  Graph shows as an example

T-Score T-Score  Is a standard score Z that is scaled to have a mean of 50  *Example graph  Is a standard score Z that is scaled to have a mean of 50  *Example graph

Scaled Score Scaled Score  A scaled score changes the numbers of test questions answered correctly, into other units of measurements.  Example table pictured.  A scaled score changes the numbers of test questions answered correctly, into other units of measurements.  Example table pictured.

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Percentile Percentile  Percentile ranks the student  Percentiles are not equal units of measurement and are not the same as percent correct on a test.  Percentile ranks the student  Percentiles are not equal units of measurement and are not the same as percent correct on a test.

Descriptive Statistics Relation to Data Descriptive Statistics Relation to Data  Organize, compile and present findings  Data literacy; understanding data formats, their interpretation, and analyzing the data.  Organize, compile and present findings  Data literacy; understanding data formats, their interpretation, and analyzing the data.

Importance of Data Literacy Importance of Data Literacy  Crucial to understand data literacy as it drives data lead decision making, helps teachers provide differentiated instruction, while supporting students with moderate to severe disabilities.  Crucial to understand data literacy as it drives data lead decision making, helps teachers provide differentiated instruction, while supporting students with moderate to severe disabilities.

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References References  Bloomenthal, A. (2023). Bell curve definition: Normal distribution meaning example in finance . Investopedia. https://www.investopedia.com/terms/b/bell- curve.asp#:~:text=Key%20Takeaways,relative%20width%20around%20the%20mean  French, B. F. (2014, January 1). Test Bias . SpringerLink. https://link.springer.com/referenceworkentry/10.1007/978-94-007-0753- 5_2998#:~:text=Definition,influences%20scores%20for%20identified%20groups.  Kaliyadan, F., & Kulkarni, V. (2019). Types of Variables, Descriptive Statistics, and Sample Size. Indian dermatology online journal , 10 (1), 82–86. https://doi.org/10.4103/idoj.IDOJ_468_18  Phelan, C., & Wren, J. (2006). EXPLORING RELIABILITY IN ACADEMIC ASSESSMENT . https://chfasoa.uni.edu/reliabilityandvalidity.htm.  Bloomenthal, A. (2023). Bell curve definition: Normal distribution meaning example in finance . Investopedia. https://www.investopedia.com/terms/b/bell- curve . asp#:~:text=Key%20Takeaways,relative%20width%20around%20the%20mean  French, B. F. (2014, January 1). Test Bias . SpringerLink. https://link.springer.com/referenceworkentry/10.1007/978-94-007-0753- 5_2998#:~:text=Definition,influences%20scores%20for%20identified%20groups.  Kaliyadan, F., & Kulkarni, V. (2019). Types of Variables, Descriptive Statistics, and Sample Size. Indian dermatology online journal , 10 (1), 82–86. https://doi.org/10.4103/idoj.IDOJ_468_18  Phelan, C., & Wren, J. (2006). EXPLORING RELIABILITY IN ACADEMIC ASSESSMENT . https://chfasoa.uni.edu/reliabilityandvalidity.htm.

Professional Development Presentation- Descriptive Statistics

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