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An Introduction to Statistics and Research Design Chapter 1.

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1 An Introduction to Statistics and Research Design Chapter 1

2 Two Branches of Statistics >Descriptive statistics Organize, summarize, and communicate numerical information > Inferential statistics Use samples to draw conclusions about a population

3 Samples and Populations >A population is the complete set of the things in which we are interested Could be any size >A sample is a set of observations drawn from the particular population A portion of the population

4 Distinguishing Between a Sample and a Population >Population of the world Population of United States or sample from the world >Population of our school or sample from our country –Population of our class or sample from our school

5 Variables >Take on a range of values An example: Reaction time in the Stroop Task >The time to say the colors compared to the time to say the word

6 Look at the following words and say each word as quickly as you can: Stroop Demonstration

7 WHITE RED GREEN BROWN

8 Stroop Demonstration, cont. >Now look at the following words and say the color of the font, not what the word says, as quickly as you can.

9 WHITE RED GREEN BROWN

10 Stroop Test >Why is the Stroop test hard? It seems we have a hard time inhibiting our reading of the word!

11 Types of Variables >Discrete Variables that can only take on specific values (e.g., whole numbers) >How many letters are in your name? Levels. >Continuous Can take on a full range of values >How tall are you?

12 More Classification of Variables >Nominal: category or name >Ordinal: ranking of data >Interval: used with numbers that are equally spaced >Ratio: like interval, but has a meaningful 0 point

13 Examples of Variables >Nominal: name of cookies >Ordinal: ranking of favorite cookies >Interval: temperature of cookies >Ratio: How many cookies are left? >What kind of data does our Stroop test give us? Interval or ratio?

14 Note: Ordinal is Almost Always discrete and Seldom continuous. (book is wrong)

15 Variables >Independent That you manipulate or categorize >Dependent That you measure; it depends on the independent variable >Confounding That you try to control or randomize away Confounds your other measures! Ex. Weight Loss, Diet, Exercise

16 Developing Research Hypotheses

17 Selecting and Assessing Variables >Operational definition >Exactly what you are studying. Operationalize “Love,” “Severity of A Cold,” “Creativity”

18 Selecting and Assessing Variables >Operational definition >Exactly what you are studying >Reliability Consistency of the measure >Validity Extent the test measures what it is supposed to measure

19 Hypothesis Testing >The process of drawing conclusions about whether a relation between variables are supported or not supported

20 Types of Research Designs >Experiments: studies in which participants are randomly assigned to a condition or level of one or more independent variables

21 Experiments and Causality >Experiments: able to make causal statements Control the confounding variables >Importance of randomization

22 Figure 1-3: Self-Selected into or Randomly Assigned to One of Two Groups: Guitar Hero Players vs. Non-Guitar Hero Players

23 Does Smoking Cause Cancer >No (Fisher), Can’t randomly assign people to smoking and no-smoking groups. Can’t rule out confounds. >Yes, Wealth of corroborating evidence. Animal models. Observational studies. Biologically testable mechanisms (look at cells, etc).

24 One Goal, Two Strategies >Between-groups designs Different people complete the tasks, and comparisons are made between groups >Within-groups designs The same participants do things more than once, and comparisons are made over time

25 Observational Research

26 Thursday March 1, 2001, 6:15 PM ET, Knee Relief May Be All in the Head, Study Finds SAN FRANCISCO (Reuters Health) - A surgical procedure used to treat arthritis of the knee may bring patients relief, but the relief may all be in patients' heads, new research results suggest. In a study of 180 people with osteoarthritis of the knee, a team of Houston surgeons found that patients who had ``sham'' arthroscopic surgery reported as much pain relief and improved mobility as patients who actually underwent the procedure. In fact, the group that did not undergo surgery reported better short-term functioning compared with the other patients, Dr. Bruce Moseley Jr. reported here at the annual meeting of the American Academy of Orthopedic Surgeons. Arthroscopic surgery for arthritis of the knee involves removing damaged tissue from the joint through small incisions. It has been unclear why the procedure helps some people with the condition. So Moseley and his colleagues at Baylor College of Medicine decided to test whether there might be an arthroscopy- associated ``placebo effect''-a psychological lift that makes patients feel better physically. In research, drugs are commonly tested against inactive pills to gauge the placebo effect, but in this case, Moseley's team led patients to believe they underwent surgery. The surgeons made small, skin-deep incisions in the patients' knees and basically ``acted out'' the surgery, Moseley explained. After 2 weeks, patients who got the sham surgery were doing better than the true surgery patients-most likely, Moseley said, because they had been spared the ``trauma'' of surgery. He reported that after 2 years, the groups had made similar gains in walking and stair climbing, and their pain had eased to comparable degrees. Because all patients had received painkilling drugs and none underwent physical therapy after their actual or sham surgery, Moseley credited the placebo effect for helping the sham-surgery group. ``I was surprised,'' he said, noting that when colleagues first proposed the possibility to him, he discounted it. ``But,'' Moseley added, ``every treatment has a specific effect-the physiological effect, and a non-specific effect-an emotional or psychological (benefit).'' While this research is not the final word on arthroscopic surgery for knee osteoarthritis, Moseley said the result does suggest it may be time for surgeons to take a closer look at it. ``We, as surgeons,'' he said, ``may need to put our time into finding better and more effective treatments.''


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