Chapter 1 Flashcards

(29 cards)

1
Q

Statistics

A

The study of methods to describe and measure aspects of nature from samples.

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2
Q

Statistical Hypothesis Testing

A

Specific claim about a population parameter

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3
Q

Population

A

All of the individuals in the world

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4
Q

Samples

A

A subset of the population of interest
- Can be individual or group of individuals

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5
Q

Parameter

A

A quantity describing a population (measurement or observation)

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6
Q

Estimate

A

A quantity calculated from a sample

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7
Q

Sampling Bias

A

A systematic difference between parameter and its estimate
- Occurs when the samples aren’t representative of the population

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8
Q

Sampling Error

A

Undirected deviation of estimates away from parameters

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9
Q

Volunteer Bias

A

Volunteers are likely to be different on average from the population

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10
Q

Properties of Good Sample

A

Random and Independent (Equal chance of selection) selection

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11
Q

Variable

A

Any characteristics or measurements that differs from individual to individual

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12
Q

Data

A

Measurement of the variables

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13
Q

What ate the two types of variable?

A

Numeric (Quantitative) and categorical (Qualitative)

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14
Q

Numeric Variable

A

Magnitude on a numeric scale

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15
Q

Categorical Variable

A

Describe members in a category or groups
1. Ordinal: can be ranked (sizes)
2. Nominal: cannot be ranked (sex chromosomes)

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16
Q

Numerical Data

A

Continuous - continued with decimals or fractions
Discrete - whole number, can be counted

17
Q

Explanatory Variable

A

Manipulated by the researcher: “Independent”

18
Q

Response Variable

A

Measured effect: “Dependent”

19
Q

Frequency Distribution

A

Shows how often each value of the variable occurs in the sample: common values, rare values, average, and variation.

20
Q

What are the two types of Probability distribution?

A

Actual and Theoretical (normal distribution)

21
Q

Actual/Real distribution is almost never known…Why not?

A

For actual, needs to measure every member of the population!

22
Q

Experimental Studies

A

Researchers assign treatments to individuals
1. Controlling a variable (placebo/non placebo)
2. Cause and effect

23
Q

Observation Studies

A

Researches do not assign treatments
1. Observe association

24
Q

Observation studies CANNOT

A

Prove causation or disentangle cause and effect

25
Why bother with observation studies?
Gather information to plan an experiments and ethics cannot do experiments such as on pregnant women and smoking
26
Confounding Variables
Variable that are not considered in an experimental study but they may affect the response variable
27
How could experimental studies remove confounding?
Through random assignment of treatment
28
Examples: "The number of violent crimes tend to increase when ice-cream sales increase" What is the confounding variable?
Heat
29
Well designed experiment can reveal causation. What could be considered as a well designed experiment?
Random assignments and artifacts (placebo effects)