'Normal curve' presentation slideshows

Advanced Quantitative Methods

Advanced Quantitative Methods. William L. Holzemer, RN, Ph.D., FAAN Professor, School of Nursing University of California, San Francisco bill.holzemer@nursing.ucsf.edu. Objectives. Develop your definition of nursing science Use the Outcomes Model to think about your area(s) of interest

2.73k views • 199 slides

Review

Review. A quick review of each chapter. Chapter 1. One-Variable Statistics. How old is our teacher?. N=82. Describe the distribution. CUSS: C enter(mean and median), U nusual features(are there outliers?), S hape(skewed left,symmetric , skewed right), S pread(max to min).

1.68k views • 139 slides

Hypothesis Testing

Hypothesis Testing. Hypothesis. An educated opinion What you think will happen, based on previous research anecdotal evidence reading the literature. Body fat level of 8th graders. National Norm: Mean = 23%, SD = 7% postulated parameter ( ? and ? )

1.09k views • 86 slides

Sample Size and Power Calculations

Sample Size and Power Calculations. Andy Avins, MD, MPH Kaiser Permanente Division of Research University of California, San Francisco. Why do Power Calculations?. Underpowered studies have a high chance of missing a real and important result Risk of misinterpretation is still very high

812 views • 52 slides

Chapter 4

628 views • 47 slides

Warsaw Summer School 2019, OSU S tudy A broad P rogram

Warsaw Summer School 2019, OSU S tudy A broad P rogram. Probability and the Normal Curve Samples and Populations. Probability distribution.

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Confidence Intervals

Confidence Intervals. Rate your confidence 0 - 100. Name my age within 10 years? within 5 years? within 1 year? Shooting a basketball at a wading pool, will make basket? Shooting the ball at a large trash can, will make basket? Shooting the ball at a carnival, will make basket?.

736 views • 37 slides

A Pragmatic Introduction to the Gaussian Curve

A Pragmatic Introduction to the Gaussian Curve. John Behrens Arizona State University Behrens @asu.edu. Version of 9/98. As we have seen, data occur in many shapes including. As we have seen, data occur in many shapes including. Positively Skewed.

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Chapter 5: Continuous Random Variables

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Data Analysis

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Computing Probabilities From the Standard Normal Distribution

Computing Probabilities From the Standard Normal Distribution. Table B.1 p. 687. Table B.1 A Closer Look. The Normal Distribution: why use a table?. From x or z to P To determine a percentage or probability for a normally distributed variable .

990 views • 25 slides

Measures of Dispersion & The Standard Normal Distribution

Measures of Dispersion & The Standard Normal Distribution. 2/5/07. The Semi-Interquartile Range (SIR). A measure of dispersion obtained by finding the difference between the 75 th and 25 th percentiles and dividing by 2. Shortcomings

747 views • 21 slides

What is intelligence?

What is intelligence?. Think of the smartest person you know. Why did you pick that person? Think of some other intelligent people. What makes them different? Intelligence is hard to nail down. Official Definition.

1.1k views • 20 slides

Use of Confidence Intervals in Performance Improvement Appeals

Use of Confidence Intervals in Performance Improvement Appeals. Performance Reporting Division Texas Education Agency. Overview of CI Process. Eligibility for application of CI Matched pairs of students Recalculate performance improvement Recalculate required improvement

388 views • 14 slides

Normal Distributions & z score

Normal Distributions & z score. Dec. 9. Normal Distribution. Tend to cluster around the mean Symmetrical bell-shaped frequency polygon Mode, median, mean all occur at the highest point, in the center of distribution

538 views • 12 slides

Standard Deviation

Standard Deviation. A measure of variability Commonly used to calculate other statistical measures Shows the distance (difference) between the mean and the steepest part of a normal curve Indicates dispersion , or spread, of scores in a distribution. Standard Deviation.

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Principles of Test Construction

Principles of Test Construction. For a psychological test to be acceptable it must fulfill the following three criteria:. Standardization Reliability Validity. Standardization.

4.72k views • 6 slides