'Required sample size' presentation slideshows

Quant 3610

Quant 3610. Weber State University. Dr. Stephen Hays Russell. Reminder on Grade Cuts. 92.01 - 100 = A 90 - 92.0 = A- 87 - 89.99 = B+ 83 - 86.99 = B 77 - 82.99 = B- 74 - 76.99 = C+ 70 - 73.99 = C 66 - 69.99 = C- 64 - 65.99 = D+ 61 - 63.99 = D 57 - 60.99 = D- Below 57.0 = E.

663 views • 52 slides

Statistical Considerations in Interventional Research

Statistical Considerations in Interventional Research. Charles E. McCulloch Division of Biostatistics. November 13, 2008. Outline. Introduction Examples Design and analysis issues Cluster randomized trials (CRTs) Statistical analysis of CRTs Design considerations for CRTs

528 views • 36 slides

Chapter 7 Confidence Intervals (application of the Central Limit Theorem)

Chapter 7 Confidence Intervals (application of the Central Limit Theorem). Introduction and Confidence Intervals for Proportions. Chapter 7 Objectives. Construct confidence intervals for population proportions based on the information contained in a single sample. Concepts of Estimation.

523 views • 33 slides

Sample Size Calculation

Sample Size Calculation. ??.??. ??????? ?????????? ????????????????? ??????????????????. Why. To complete research proposal Reduce unnecessary expense (time, labor, money, materials) Avoid useless research. Type of Experiment. 1. Survey Observational Study 2. Test a Hypothesis

1.26k views • 32 slides

Interval estimates of the mean for small n, ? unknown. Estimates of sample size.

358 views • 25 slides

Interval Estimation Part II

Interval Estimation Part II. Notes of STAT6205 by Dr. Fan. Overview. Sections 6.4 to 6.6 Introduction Confidence Intervals for variances One variance Ratio of two variances Confidence Intervals for proportions One proportion Difference of two proportions Sample size.

315 views • 19 slides

330 views • 18 slides

Understanding sample survey data

Understanding sample survey data. Underlying Concept. A sample statistic is our best estimate of a population parameter If we took 100 different samples from the same population to measure, for example, the mean height of men, we would get a 100 different estimates of mean height.

298 views • 18 slides

Ch. 8: Confidence Interval Estimation

Ch. 8: Confidence Interval Estimation. In chapter 6, we had information about the population and, using the theory of Sampling Distribution (chapter 7), we learned about the properties of samples. (what are they?)

639 views • 14 slides

Ch. 8: Confidence Interval Estimation

Ch. 8: Confidence Interval Estimation. In chapter 6, we had information about the population and, using the theory of Sampling Distribution (chapter 7), we learned about the properties of samples. (what are they?)

261 views • 14 slides

212 views • 13 slides

5.3 Determining Sample Size to Estimate p

5.3 Determining Sample Size to Estimate p. To Estimate a Population Proportion p. If you desire a C% confidence interval for a population proportion p with an accuracy specified by you, how large does the sample size need to be?

680 views • 10 slides

5.3 Determining Sample Size to Estimate p

5.3 Determining Sample Size to Estimate p. To Estimate a Population Proportion p. If you desire a C% confidence interval for a population proportion p with an accuracy specified by you, how large does the sample size need to be?

110 views • 10 slides