CLD9003 Statistics in Modern Society

CLD9003Statistics in Modern Society

Alan Lam

Dept of CDS

CLD9003 Statistics in Modern Society

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Course Outline

• A General Education course

• Sectional Approach– Class discussion (Major Emphasis)

• Course text– Bennett, J.O., Briggs, W.L. and Triola, Mario

F. 2014 Statistical Reasoning for Everyday Life, 4/E, Addison-Wesley.


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Course Outline

• Tentative Schedule

• Software– Excel/SPSS

• Assessment– Attendance 5%– Group Project 20%– Participation 15%– Examination 60%

GED111/CDS111 Statistics in Modern Society

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What Is/Are Statistics

• Two Definitions– Statistics is the science of collecting,

organising, and interpreting data.– Statistics are the data that describe or

summarize something.


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How does it work?

• Advertising– Claim of 111.3 million watched a TV program– Survey of 5000 homes

• Goal – population– The population in a statistical study is the

complete set of people or things being studied.

– Population parameters• Specific characteristics of the population• Mean, median, mode, standard deviation, size, etc.


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What actually gets studied?

• Sample– A subset of the population from which data

are actually obtained– Sample statistics

• Characteristics of the sample found by consolidating or summarizing the raw data

• Mean, median, mode, standard deviation, size, etc.

– Raw data• The actual measurements or observations

collected


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How do sample statistics relate to population parameters?

• Estimation / Inferential statistics– Margin of error

• The sample represents the population fairly• The margin of error is generally smaller for a larger

sample– 10% for sample size of 100– 5% for sample size of 400– 3% for sample size of 1,000– 1 % for sample 10,000


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Margin of Error

• Used to describe the range of values likely to contain the population parameter.

• The range is found by sample ± margin of error

• From (sample statistic – margin of error) to (sample statistic + margin of error)


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The Process of a Statistical Study

Start

Population Sample

Sample StatisticsPopulation Parameters

1 Identify goals

2 Draw from population

3 Collect raw data and summarize

4 Make inferences about population(estimation)

5 Draw conclusions


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Decisions for an Uncertain World

• Decision making under uncertainty– Ad hoc case with no historical record– One off decision making


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Exercises

• 11. Stem Cell Research p.9

• 13. Galactic Distances p.9

• 21. Do People Lie About Voting? P.10

• Exercise– 24, 25, 26 (p.10)


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Sampling

• Census– The collection of data from every member of a

population• Sampling

– Collection of data from part of the population• Representative Sample

– The relevant characteristics of the sample members are generally the same as the characteristics of the population

• Bias– If a statistical study’s design or conduct tends to

favour certain results


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Sampling Methods

• Simple Random Samples– Assign number to every possible outcome and each

outcome is equally likely to be selected

• Systematic Sampling– Selection made every nth possible outcomes

• Convenience Samples– Based on the convenience of selection– More prone to bias than most other forms of sampling


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Sampling Methods

• Cluster Samples– Selection of all members in randomly selected

groups

• Stratified Samples– Population is divided into strata (subgroup)– Selection is made from each stratum and

combined to form the sample


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Summary of Sampling Methods

• Regardless of how a sample is chosen, the study can be successful only if the sample is representative of the population

• A biased sample is very unlikely to be a representative sample

• A well-chosen sample has a good chance of being representative, but still may turn out to be biased just because of bad luck in the actual drawing of the sample


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Exercises

• Census or not– 7. You want to determine the mean GPA of

the 50 students in a particular high school Maths class

– 8. You want to determine the mean GPA of all high school senior in USA

– 9. You want to determine the mean annual energy costs of all homes in Missouri

– 10. You want to determine the mean temperature of coffee server at Starbucks


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Exercises

• Identifying the Sampling Methods p.19– 23-32

• Choosing a Sampling Methods p.20– 39-42


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Types of Statistical Studies

• Observational Study– Observe or measure characteristics of the subjects,

but do not attempt to influence or modify these characteristics

• Experiment– Apply some treatment and observe its effects on the

subject of the experiment

• Meta-analysis– Study a topic that has been the subject of many

previous studies


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Observational Study :Retrospective Studies (Case-Control

Study)• A retrospective study is an observational study

that resembles an experiment because the sample naturally divides into two (or more) groups. The participants who engage in the behaviour under study form the cases, like a treatment group in an experiment. The participants who do not engage in the behaviour are the controls, like a control group in an experiment.

• Usually uses data from the past, such as official records or past interviews.

Observational Study :Prospective Studies (Longitudinal

study)• Designed to collect observations in the

future from groups that share common factors


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Experiment :Treatment & Control Groups

• Treatment group– The group of subjects who receive the

treatment being tested

• Control group– The group of subjects who do not received

the treatment being tested.

• To assign treatment & control groups– Randomisation– Large number of subjects


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Confounding Factor

• The effect of different factors are mixed so that we cannot determine the effects of the specific factors we are studying.

• The factors that lead to the confusion are called confounding factors.


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Placebo Effect

• It refers to the situation in which patients improve simply because they are receiving a useful treatment

• A placebo lacks the active ingredients of a treatment being tested in a study, but is identical in appearance to the treatment. Thus, study participants cannot distinguish the placebo from the real treatment.


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Experimenter Effects

• Occurs when a research or experimenter somehow influences subjects through such factors as facial expression, tone of voice, attitude.

• Blinding– Single-blind– Double-blind


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Exercises

• Observational – case-control study?

• Experiment – treatment/control groups?

• Meta-analysis– Ex 10, 12, 13, 14 (p.32)

• Anything wrong? – Ex 21, 22, 24, 25, 27 (p.32)


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Should you believe a Statistical Study?

• Eight Guidelines for Critically Evaluating a Statistical Study


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The guidelines

• 1. Get a big picture view of the study– What was the study designed to determine?– The population?– Observation, experiment, meta-analysis?


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The guidelines (cont.)

• 2. Consider the source, particularly with regard to whether the researchers may be biased– Peer review

• Several experts in a field evaluate a research report before the report is published

• Published journal


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• 3. Look for Bias in the sample– Selection bias– Participation bias

• Self-selected surveys/voluntary response surveys


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• 4. Look for problems in defining or measuring the variables of interest, which can make it difficult to interpret any reported results.– Variable is any item or quantity that can vary

or take on different values– Variables of interest in a statistical study are

the items or quantities that the study seeks to measure


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• 5. Watch out for confounding variables that can invalidate the conclusions of a study


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• 6. Consider the setting and wording of any survey, looking for anything that might tend to produce inaccurate or dishonest responses.– Badly worded survey– Sensitive information


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• 7. Check that results are fairly represented in graphics and concluding statements, because both researchers and media often create misleading graphics or jump to conclusions that the results do not support.– Personal bias– Unwarranted conclusions


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• 8. Stand back and consider the conclusions. – Did the study achieve its goal?– Do the conclusions make sense?– Can you rule out alternative explanations for

the results?– If the conclusions make sense, do they have

any practical significance?


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Focus on Sociology

• Does Daycare Breed Bullies pp45-48

Documents

CLD9003 Statistics in Modern Society