'Sample elements' presentation slideshows

Logistic Regression

1.44k views • 65 slides

The Scientific Study of Politics (POL 51)

535 views • 41 slides

Tomas Oliva

296 views • 29 slides

Sampling

Sampling. Why, when?. If we would like to draw conclusions on a target population but examining the total of it is not reasonable or not feasible: Too expensive (cost, time, other resources)

230 views • 22 slides

Data Collection

Data Collection. Objectives :. At the end of this lesson, the student should be able to: 1. recognize the importance of data gathering; 2. distinguish primary from secondary data sources; 3. define population and sampling; 4. define census and sample;

563 views • 19 slides

Analysis & Interpretation: Multiple Variables Simultaneously

Analysis & Interpretation: Multiple Variables Simultaneously. Chapter 13, Student Edition. Learning Objectives. Discuss why a researcher might conduct a multivariate analysis Explain the purpose and importance of cross tabulation

440 views • 17 slides

Stratified Sampling

Stratified Sampling. Lecturer: Chad Jensen. Sampling Methods. SRS (simple random sample) Systematic Convenience Judgment Quota Snowball Stratified Sampling. What is Stratified Sampling?.

639 views • 16 slides

Sampling Basics, Nonprobability and Simple Random Samples

Sampling Basics, Nonprobability and Simple Random Samples. Chapter 15. Six-Step Procedure for Drawing a Sample. Define the Target Population. Step 1. Identify the Sampling Frame. Step 2. Select a Sampling Procedure. Step 3. Determine the Sample Size. Step 4. Select the Sample Elements.

364 views • 14 slides

Finding hot-lists

75 views • 7 slides

Adaptive Sampling

Adaptive Sampling. Based on a hot-list algorithm by Gibbons and Matias (SIGMOD 1998) Sample elements from the input set Frequently occurring elements will be sampled more often Sampling probability determined at runtime, according to the allowed memory usage

231 views • 3 slides

Introduction Inserted text from source

79 views • 1 slides