Systematic Inquiry list PDF

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List of critical concepts to understand for examination....

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Systematic Inquiry list 1. Seven survival skills a. Critical thinking and problem solving b. Collaboration across networks and leading by influence c. Agility and adaptability d. Initiative and entrepreneurialism e. Accessing and analyzing information f. Effective oral and written communication g. Curiosity and imagination h. Can Porter clean? Louisa and Alexandra interpret easily. Eager oboe water closet. Alexandra Alexandra I call I. 2. Sources of knowledge a. Personal experience b. Reason and intuition c. Authority d. Tradition e. Systematic inquiry f. Pet a siri, get knowledge 3. Characteristics of systematic inquiry a. Objectivity b. Control for bias c. Verifiable d. Inductive e. Precise f. Truthful g. Willingness to change h. Systematic inquiry is the search for knowledge by using recognized methods in data collection, analysis, and interpretation. i. The purpose of systematic inquiry is to explain natural phenomena, to understand the underlying relationships among phenomena, and to use this information to predict and influence behavior j. C TWO VIP systematically inquiring about what is up 4. Research design a. Quantitative i. Non experimental 1. Descriptive 2. Comparative 3. Correlational 4. Ex post facto a. NEED CC: cared about quantitative things like her weight ii. Experimental 1. True experimental 2. Quasi-experimental 3. Single subject b. Qualitative

i. Case study ii. Ethnography iii. Phenomenology iv. Grounded theory 5. Three conditions that must be met before someone can be said to know something is that what someone says is true, that they must be sure that what they are saying is true, and that this belief must be justified. Knowledge is often portrayed as black and white, but it is in a matter of degrees. 6. People cannot distinguish true findings from their opposite. Knowledge of outcome increases the feeling of obviousness. 7. Quantitative research question identifies the variables, the relationship between them, and the subjects. a. VRS 8. Qualitative research question identify the central phenomenon, the participants, and the site/ setting. a. CPPS 9. Words of estimative probability attempt to give the listener a legitimate grasp on one’s understanding. a. Scale for words of estimative probability i. Impossible ii. Nearly impossible iii. Very unlikely iv. Unlikely v. Chances about even vi. Likely vii. Very likely viii. Nearly certain ix. Certain 10. Your best bet for getting a fix on causation is through a randomly assigned experimental study. 11. Bottom line: question authority. Even authority wears a lab coat. 12. Reliability is a necessary but insufficient condition for validity. Factors that influence reliability are what you measure, the instrument you use, and your technique. a. What you measure i. Physical traits (most reliable) ii. Cognitive traits (less reliable) iii. Affective traits (least reliable) b. Scales of measurement i. Nominal (categorical) ii. Ordinal (categorical) iii. Interval (continuous) iv. Ratio (continuous) 13. People tend to regard as obvious any reasonable statement about human behavior, particularly when you provide data, “evidence”, for it 14. If there are strong correlations between A and B, you can predict A through B if that information is easier to access or cheaper

15. 20th century rewards and motivators that we think are a natural part of business only work in a surprisingly narrow band of circumstances. If-then rewards often destroy creativity. And the secret to high performance isn’t rewards and punishments, but the unseen intrinsic drive of doing things for their own sake because they matter. 16. The most effective elements for getting us to increase our motivation for 21st century tasks are mastery, autonomy, and purpose. 17. Statistics: procedures used to summarize and analyze quantitative data 18. Descriptive statistics: procedures use to summarize a set of numbers in terms of central tendency, variation, or relationships i. Types of descriptive statistics 1. Central tendency: the typical score (the best bet) 2. Variability: how different the scores are 3. Correlation coefficient: a measure of the relationship between two variables 4. Z-score: the relationship of one score to the norm group in terms of standard units 5. Effect size: a measure of the magnitude and difference of the means of two groups** what you care about is the effect size a. CV CE Z and describes her statistically as beautiful b. Central tendency variability correlation effect size z-score c. Describe a good song to me about statistics. Sing this like a scale: CVCEZ 19. Inferential statistics: procedures used to determine the error when estimating a value for a population based upon the measurement of the same value for a sample of that population (“this is the correct answer, plus or minus a certain amount”). 1. The purpose of inferential statistics is to make conclusions about some value of a population on the basis of that same value measured for a sample. (inferring something about the population based on the sample) 2. Inferential statistics allow us to estimate the magnitude of our error —the difference between the sample value and the population value—even though we don’t know what the population value is

3. One estimate of error is the “confidence interval”—a range within which the true value is likely (%) to be. The wider the range, the higher the confidence level. 20. People judge their wine on three things, mainly—price, ratings, and brand. (PRB) 21. Things to consider as related to the sample: how was the sample selected? Is this sample representative of the population that these findings are extended to? 22. A subject or participant: a person from whom data are collected. Generally, qualitative is participant, subject is quantitative. 23. Sample: a collective group of subjects or participants from whom data are collected. 24. Population: a large group of individuals to whom the results of a study are generalized. 25. The two types of sampling procedures are probability, which is generally used in quantitative research, and non-probability, which is generally used in qualitative research. 26. The goal of a quantitative sample are to select a sample that is representative of the population that you will generalize your results to, and to reduce sampling error and bias. Sampling error is the difference between the true result and the observed result, that can be attributed to using samples rather than the population. Sampling bias is the differences between the true and observed results that can be attributed to errors on the part of the researcher. The goals for qualitative sampling are to select participants that are knowledgeable about the topic/ phenomenon you are researching. 27. Strategies for quantitative sampling a. Simple random b. Stratified sampling i. Proportional stratified sampling ii. Disproportional stratified sampling c. Cluster sampling d. Convenience sampling i. RANDOMLY, I had a SAMPLE of peanut CLUSTERS at a CONVENIENCE STORE. They were SIMPLY delicious, so I went STRAIT to buy a massive QUANTITY. ii. Randomly, I had a sample of peanut clusters. They were simply delicious. I went strat to the convenience store to buy a massive quantity. 28. Key first step in quantitative sampling: define the target population 29. Strategies for qualitative sampling a. Typical case b. Extreme case c. Maximum variation d. Snowball (aka networking)- someone tells you to talk to someone, who directs you to someone else, and so on and so forth e. Critical case i. C STEM ii. It is CRITICAL that we have the TYPICAL QUALity of SNOW on the mountain this year. If we have EXTREME snowfall or a MAXIMUM VARIATION of snowfall, someone could get hurt.

iii. It is critical that we get the typical amount of snowfall this year. If we have extreme amounts of maximum variation in the quality, someone could get hurt. 30. Reliability: consistency of (accurate) measurement 31. Validity: how meaningful, useful, and appropriate our conclusions are 32. The purpose of experiments is to establish a strong argument for a cause and effect relationship between two variables—that a change in one directly causes the change in another. 33. The characteristics of experiments are direct manipulation of the independent variable and control of extraneous variables. 34. Forms of validity: validity, internal validity, external validity. 35. Internal validity: the extent to which the independent variable, and not other extraneous variables, produces the observed change in the dependent variable (how confident you are that by manipulation this variable, you produce this change in the other variable). 36. External validity: the extent to which the results of a study can be generalized to other subjects, settings, and time. 37. Internal validity is a necessary but insufficient condition for external validity. a. Strong experimental design: “randomized pretest- posttest control group design” i. Experimental group

Opre

X

Opost

Opost2

Opre

—

Opost

Opost2

ii. Random assignment of subjects iii. Control group

b. We use a control group to help reduce threats to internal validity c. We randomly assign subjects to help ensure equivalence between the two groups… on the dependent measures as well as all others d. We use a pretest to test for equivalence of groups at the start and for baseline data to calculate pretest/ posttest data e. What treatments to the subjects get? The experimental group gets the treatment of course, and the control group gets something unrelated to the dependant variable (longtoss and visualization on arm strength—what the placebo group gets should not affect the dependent variable) f. We use a posttest to measure the delta between the pretest and posttest and to measure the delta between groups on the posttest g. Strong experimental design also includes a delayed retention test to determine whether the effects are lasting or fade quickly

h. You measure the difference between Opost and Opost and test for effect size and statistical significance 38....