'Simple random sample srs' presentation slideshows

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Chapter 4: Gathering Data

Chapter 4: Gathering Data. Section 4.1 Should We Experiment or Should We Merely Observe?. Learning Objectives:. Population versus Sample Types of Studies: Experimental and Observational Comparing Experimental and Observational Studies. Learning Objective 1: Population and Sample.

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Chapter 5

Chapter 5. Producing Data. Objectives:. Distinguish between, and discuss the advantages of, observational studies and experiments. Identify and give examples of different types of sampling methods including a clear definition of simple random sample.

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Data Collection and Presentation

Data Collection and Presentation. Still John F. Reyes. PART 1. Methods of Data Collection. Characteristics of a Good Question A good question is unbiased.

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APSTAT Section 3 Experimental Design

APSTAT Section 3 Experimental Design. Chapter 11 Simulation. HOW TO SET UP Describe the experiment Assumptions Independence Percentages Randomization Assign Digits (Table) Explain TI83 procedure Conduct Multiple Simulations Conclusion (Estimate Probability).

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213Sampling.pdf

213Sampling.pdf. When one is attempting to study the variable of a population, whether the variable is qualitative or quantitative, there are two methods of data collection which can be employed: 1. Conduct a Census. 2. Take a Sample. Some Population characteristics:

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STA 291 Fall 2008

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Review

Review. Observational study and Experiment Individuals, population and sample Sample survey and Census. Review. Observational Study Observes individuals and measures variables of interest but does not attempt to influence the responses. Experiment

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The School of Nursing and Midwifery

Cross-Sectional Studies. The School of Nursing and Midwifery. Professor Catherine Comiskey. Learning Outcomes. Develop an understanding of: What a cross-sectional study is Point Prevalence Rates Basic methodology Advantages and disadvantages. Cross-sectional Studies.

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AP Statistics

AP Statistics. 5.1 Designing Samples. Learning Objective:. Differentiate between an observational study and an experiment Learn different types of sampling techniques Use a random digit table to create an SRS Understand different types of bias. Definitions.

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5-Minute Check on Activity 7-4

5-Minute Check on Activity 7-4. Given the following data: 8, 1, 9, 2, 3, 4, 4, 5, 5, 6, 7, 8, 8 Find the mean Find the median Find the mid-range Find the mode What are the four descriptors of a distribution? What are the three types of shape? Which measures of center are resistant?.

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The Logic of Sampling

The Logic of Sampling. Key Sampling Concepts. Sampling (two types) Element Population Sample Sampling Frame Representative Sample. Application of Sampling Terms. Types of Samples. Probability -- Strictly following two rules. Non Probability -- Failing to follow the two rules.

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Getting Started Chapter 1

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Topic 1 Collecting and Producing Data

Topic 1 Collecting and Producing Data. Basically, 3 parts to this topic. All three are important and fundamental to statistics Sampling methods Design of studies Simulations. What to take away from Chapter 1 of your textbook. Relevance of statistics in our daily lives Variability

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Section 11.1 Inference for the Mean of a Population

Section 11.1 Inference for the Mean of a Population. AP Statistics. Inference for the Mean of a Population.

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Chapter 5 Sampling and Surveys

Chapter 5 Sampling and Surveys. 5.1 Samples, Good and Bad. Bias . Design flaw of a statistical study that systematically favors certain outcomes. Systematically favoring one outcome over another. Samples. Sample is a small group from a larger population.

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Stat 13, Thu 5/10/12. 1. CLT again. 2. CIs. 3. Interpretation of a CI. 4. Examples.

Stat 13, Thu 5/10/12. 1. CLT again. 2. CIs. 3. Interpretation of a CI. 4. Examples. 5. Margin of error and sample size. 6. CIs using the t table. 7. When to use z* and t*. Read ch. 5 and 6. Hw5 is due Tue, 5/15. Midterm 2 is Thur, 5/17.

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Chapter 1:

Chapter 1:. Sampling and Descriptive Statistics. Why Statistics?. Uncertainty in repeated scientific measurements Drawing conclusions from data Designing valid experiments and draw reliable conclusions. Section 1.1: Sampling. Definitions:

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Ch. 5 Taking a Simple Random Sample

Do Now: 1. Take out HW. 2. Copy down HW. 3. What are the types of Bias and Sampling Error we discussed last class? Explain what they are. Ch. 5 Taking a Simple Random Sample. SRS Day 1. Why do we sample?. -We sample because we want to know something about our population.

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Chapter 12: Sample Surveys There is no recovery from poorly collected data!

Chapter 12: Sample Surveys There is no recovery from poorly collected data!. "An approximate answer to the right question is worth a good deal more than the exact answer to an approximate question." John Tukey. Overview.

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