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Getting Started Chapter 1 Understandable Statistics Ninth Edition By Brase and Brase Prepared by Yixun Shi Bloomsburg University of Pennsylvania.

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Presentation on theme: "Getting Started Chapter 1 Understandable Statistics Ninth Edition By Brase and Brase Prepared by Yixun Shi Bloomsburg University of Pennsylvania."— Presentation transcript:

1 Getting Started Chapter 1 Understandable Statistics Ninth Edition By Brase and Brase Prepared by Yixun Shi Bloomsburg University of Pennsylvania

2 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 2 What is Statistics? Collecting data Organizing data Analyzing data Interpreting data

3 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 3 Individuals and Variables Individuals are people or objects included in the study. Variables are characteristics of the individual to be measured or observed.

4 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 4 Variables Quantitative Variable – The variable is numerical, so operations such as adding and averaging make sense. Qualitative Variable – The variable describes an individual through grouping or categorization.

5 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 5 Data Population Data – The variable is part of every individual of interest. Sample Data – The variable is part of only some of the individuals of interest, i.e. of just a part of the population.

6 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 6 Levels of Measurement Nominal – The data that consist of names, labels, or categories. Ordinal – The data can be ordered, but the differences between data values are meaningless.

7 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 7 Levels of Measurement: Interval Interval – The data can be ordered and the differences between data values are meaningful. Ratio – The data can be ordered, differences and ratios are meaningful, and there is a meaningful zero value.

8 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 8 Critical Thinking Reliable statistical conclusions require reliable data. When selecting a variable to measure, specify the process and requirement for the measurement. Pay attention to the measurement instrument and the level of measurement. Are the data from a sample or from the entire population?

9 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 9 Two Branches of Statistics Descriptive Statistics: Organizing, summarizing, and graphing information from populations or samples. Inferential Statistics: Using information from a sample to draw conclusions about a population.

10 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 10 Sampling From a Population Simple Random Sample of size n –Each member of the population has an equal chance of being selected. –Each sample of size n has an equal chance of being selected.

11 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 11 Sampling Techniques Simple random sampling Inappropriate sampling ( asking patrons in a mall to participate in a survey, soliciting volunteers in a newspaper ad to taste test a new snack food, etc ) Systematic sampling

12 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 12 Sampling Techniques Stratified sampling Cluster sampling Convenience sampling

13 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 13 Critical Thinking Sampling frame – a list of individuals from which a sample is selected. Undercoverage – resulting from omitting population members from the sample frame. Sampling error – difference between measurements from a sample and that from the population. Nonsampling error – result of poor sample design, sloppy data collection, faulty measuring instruments, bias in questionnaires, and so on.

14 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 14 Guidelines For Planning a Statistical Study 1.Identify individuals or objects of interest. 2.Specify the variables. 3.Determine if you will use the entire population. If not, determine an appropriate sampling method 4.Determine a data collection plan, addressing privacy, ethics, and confidentiality if necessary.

15 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 15 Guidelines For Planning a Statistical Study 5.Collect data. 6.Analyze the data using appropriate statistical methods. 7.Note any concerns about the data and recommend any remedies for further studies.

16 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 16 Census vs. Sample In a census, measurements or observations are obtained from the entire population (uncommon). In a sample, measurements or observations are obtained from part of the population (common).

17 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 17 Observational Study Measurements and observations are obtained in a way that does not change the response or variable being measured.

18 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 18 Designed Experiments A treatment is applied to the individuals in the experiment in order to observe a potential effect on the variable being measured Designed experiments are used to pin down a cause-and-effect relationship. To measure the effect of a treatment, statisticians may break the individuals into treatment group and control group.

19 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 19 Designed Experiments Placebo Effect Lurking Variable Blocking Randomization Blind Experiments Double-Blind Experiments

20 Copyright © Houghton Mifflin Harcourt Publishing Company. All rights reserved.1 | 20 Surveys Collecting data from respondents through interviews, phone conversations, internet polls, mail polls, etc… Non-response: Respondents cannot be contacted or refuse to answer. Voluntary response surveys: May be biased due to strong opinions held by those willing to participate. Survey results usually cannot pin down a cause-and-effect relationship.


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