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Statistics w Swingle > Exam 1 > Flashcards

Exam 1 Flashcards

Visual Displays, Probability and Frequency (56 cards)

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1
Q

Descriptive Statistics vs Inferential Statistics

A

Summarizing and Exploring Data vs Making inferences based on data

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2
Q

Population : WEAK

A
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3
Q

Sample: WEAK

A
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4
Q

Theory

A

Answers a how or why question. Unlike laws, theories have not been repeatedly verified. Note, PSET 1, Law of Supply and Demand is considered a widely agreed upon THEORY

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5
Q

Concepts: Weak definition

A

The elements and ideas behind a theory

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6
Q

Hypothesis

A

A prediction

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7
Q

Variable

A

Makes up a hypothesis.. A characteristic that can very among subjects within a population

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8
Q

instrument

A

a measurement device used to measure variables

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9
Q

unit of analysis

A

the thing about which we are collecting information. A unit of analysis has variable characteristics that we analyze

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10
Q

Units of Measurement

A

used to record measurements of the variable

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11
Q

Independent Variables vs Dependent Variables

A

Cause variables vs effect variables

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12
Q

4 types of relationships between variables

A
  1. Positive
  2. Negative
  3. Linear / Non linear
  4. Statistically Significant (p values)
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13
Q

Mutually Exclusive

A

You can only select ONE option ( I can only be born in New York)

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14
Q

Collectively Exhaustive **

A

All categories are there and included

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15
Q

Qualitative Variables

A

Scale of measurement is a set of unordered categories
Categories differ in quality not quantity

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16
Q

Quantitative

A

Numerical
Set of Ordered Categories
Categories differ in quantity and/or magnitude

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17
Q

Discrete

A

Integer Values

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18
Q

Continuous

A

Can be any real value, can be subdivided (measurement rather than counting typically)

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19
Q

NOIR

A

Nominal: Are there different values
Ordinal: Can we order the variables
Interval: Can we measure the distance between the variables
Ratio: Is there a meaningful zero so that you can say something is 2 times as large

Qualitative variables can only be ordinal

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20
Q

Cross Sectional Data

A

Observations on different units taken at a snap shot

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21
Q

Time Series

A

Observations on a variable over time

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22
Q

Pooled Cross Sectional

A

Data from multiple years (multiple snapshots)

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23
Q

Panel / Longitudinal Data

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A

Follows units within a cross section over a given period of time

24
Q

Visual Displays (5.)

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A
  1. Unit of Analysis in Rows
  2. Variables in Columns
  3. Zero Origin (Non Zero Misleading)
  4. Proper Scaling of Axes
  5. Sourced specific data
25
Grouped Frequency Distribution: 50 - 59
49.5 : Lower Class Boundary 50: Lower Class Limit 59: Upper Class Limit 59.5: Upper Class Boundary
26
Ogive *WEAK*
Representation of cummulative frequencies
27
Stem and Leaf Plots
A Vertical Frequency Chart Left side of the line: first one or two digits (creating a category) Right Side of Line: last digits of all the numbers that are in the first 1-2 digit categories
28
Histogram: WEAK
Frequency Distribution in Bar form
29
Sturges Rules
Used to calculate appropriate # of bins for histogram When you double n, you can add another bin of bins: 1 + 3.3ln(n)
30
Mode
- Most frequent - There can be multiple modes - Works for NOIR (nominal data)
31
Median
- p(50) position - can be determined for OIR - Usually unique - Generally uneffected by outliers
32
Mean
- Works for OIR - Unique - Can be affected by outliers
33
Box Plots
Illustrate frequency distributions Box is p(25),p(50),p(75) Lower fence is p(25) - 1.5(p(75)-p(25)) Upper fence is p(75) - 1.5(p(75)-p(25))
34
trimmed mean
mean calculated by removing outliers
35
range
difference between max and min greatly impacted by outliers
36
average deviation from the mean
each datapoint's difference from mean divided by n (problematic bc it will =0)
37
average absolute deviation
the absolute value of each datapoint's difference from mean divided by n
38
Average Square Deviation: Variance
each datapoint's difference from mean squared and then divided by n (problematic bc it will =0)
39
Standard Deviation
the square root of each datapoint's difference from mean squared and then divided by n
40
Coefficient of Variation
How different is this value from the average? stdev/mean * 100 used when you are comparing two or more variables OR two or more groups
41
z scores
how many standard deviations away from the mean is a value value - mean / std dev two or more individual VALUES on different scales
42
chebyshev's theorem
for any set of data and any k>1 , at least 1 - 1/k^2 of data must lie within k standard deviations of the mean
43
Emprical Rule
With normal distributions (bell shaped) z score 1: 68% 2: 95% 3: 99.7%
44
Combination
An unordered sample (n r) = n!/r!(n-r)!
45
Permutations
Order matter! n!/(n-r)!
46
Random Experiment
the process by which an observation is obtained. There must be at least 2 possible outcomes and there must be uncertainty
47
Basic Outcome
the result of a random experiment
48
Sample Space
set of all basic outcomes
49
Event
Combination of one or more basic outcomes
50
Complement
outcomes in a sample space not contained by the event
51
Empirical Probability
Possible w/ no prior knowledge of events (think medical data.. how many ppl are born etc)
52
Subjective Probability
Based on past experience, essentially a prediction
53
Classical Probability
Based on deduction Think dice and coins
54
Subtraction Rule
P(A) + P(A comp) = 1
55
Statistical Independence
1. the probability of one event is not impacted by the probability of another P(A) = P(AIB) 2. Another way to determine is if the percentage of group A in the general pop is = to the percentage in group B NOTE: mutually exclusive is NOT statistically independent
56
Multiplication Rule
P(AIB) * P(B) = P (A and B) P(BIA) * P (A) = P(A and B)

Statistics w Swingle (2 decks)

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