Chptr 3 & 4 Study Guide Flashcards

1
Q

Mean

A

(μ, x̄) sum of data values / # of values; x̄ = ( Σx ) / n

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2
Q

Mode

A

value(s) w/ greatest occurring frequency; qualitative and quantitative; doesn’t get rounded; possible for no modes or more than one modes

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3
Q

Median

A

middle value when original data values are in increasing / decreasing order; resistant & doesn’t directly use every data value; find mean of two medians when even number set

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4
Q

Midrange

A

Max value + min value /2; not resistant

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5
Q

Range

A

max value - min value; non-resistant; doesn’t use all data sets

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6
Q

Variance

A

set of values is a measure of variation equal to the square of the standard deviation; nonresistant, squares of the units of the original data values, never negative, unbiased estimator
• Sample s^2= square of the standard deviation s.
• Population variance σ ^2= square of the population standard deviation

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7
Q

Round-off Rule for Measures of Center

A

mean, median, and midrange = carry one more decimal place than is present in the original set of values.
mode = leave the value as is without rounding

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8
Q

Standard deviation

A

(s) a measure of how much data values deviate away from the mean ; never negative, larger values = more variation, nonresistant, same units as original data, biased estimator
- s sample = √Σ (x - μ)^2 / n - 1
- σ (population) = √Σ (x - μ)^2 / N)

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9
Q

Locate mode, median, and mean in bell-shaped, positive, and negative-skewed distribution

A

normal: mean, median, mode are all in the center
positively skewed: mean = center; median = btwn mode + mean; mode = far left (top of slope)

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10
Q

Resistant

A

presence of extreme values (outliers) doesn’t cause it to change very much

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11
Q

Resistant measures of center

A

median, mode

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12
Q

Nonresistant measures of center

A

Mean, midrange, range, variance, standard deviation

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13
Q

z score

A

(z) How many standards deviations away it is from the mean (round to two decimal places);
- sample: x - x̄/s
- population: x - x̄/σ

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14
Q

When is the standard deviation of a data set zero if ever?

A

when all values are exactly the same

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15
Q

weighted mean

A

x̄ = Σ(wx)/Σw

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16
Q

When to use a weighted mean

A

When different r data values are assigned

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17
Q

Range Rule of Thumb

A

If I got 2 standard deviations up or down from the mean, it represents 95% of the sample values; applies to all shapes
- Significantly low values: μ - 2σ or lower.
- Significantly high values: μ + 2σ or higher.
- Values not significant: Between (μ - 2σ) and (μ + 2σ)

18
Q

Empirical Rule

A

for data sets having a distribution that is approximately bell-
shaped, (mean + or - (1,2,3,)SD)
- About 68% of all values fall within 1 standard deviation of the mean.
- About 95% of all values fall within 2 standard deviations of the mean.
- About 99.7% of all values fall within 3 standard deviations of the mean.

19
Q

Coefficient of Variation

A

(CV) for a set of nonnegative sample or population data, expressed as a percent, describes the standard deviation relative to the mean;
- sample: s/x̄ (100)
- population: σ/x̄ (100)

20
Q

First Quartile

A

(Q1, P25) It separates the bottom 25% of the sorted values from the top 75%.

21
Q

Second Quartile

A

(Q2, P50) same as the median; it separates the bot-
tom 50% of the sorted values

22
Q

Third Quartile

A

(Q3, P75) it separates the bottom 75% of the sorted
values from the top 25%.

23
Q

Interquartile Range

A

(IQR) = Q3 - Q1

24
Q

5-number summary

A
  1. Minimum
  2. Q1
  3. Q2
  4. Q3
  5. Maximum
25
Q

Percentile

A

kth percentile being used

26
Q

In a modified boxplot, a data value is an outlier if it is

A
  • above Q3, by an amount greater than 1.5 X IQR
  • below Q1, by an amount greater than 1.5 X IQR
27
Q

Boxplot

A

Box like graph that consists of the 5- number summary

28
Q

Probability

A

btwn 0 & 1;

1 = certain to happen;
->1 = more likely to happen
->0 = less likely
0 = no chance

29
Q

event

A

any collection of results or outcomes of a procedure.

30
Q

simple event

A

outcome or an event that cannot be turther broken down into simpler components (one instance only)

31
Q

Sample space

A

procedure consists of all possible simple events. That is,
the sample space consists of all outcomes that cannot be broken down any further; HHH, HHT, HTT, TTT

32
Q

Law of Large Numbers

A

“As procedure is repeated again and again, relative frequency probability of an event tends to approach the actual probability.”

33
Q

Compliment

A

All outcomes in which event A does NOT occur

34
Q

Relative Frequency Approx of Probability

A

P(A) = # of times A occurred / # time experiment repeated

35
Q

Classical Probability

A

P(A) = # of ways A occurred / # of different simple events

36
Q

biased estimator

A

they do not target the value of the corresponding population parameter; (Median, Range, Standard deviation )

37
Q

unbiased estimator

A

they each target the value of the corresponding population parameter (with a sampling distribution having a mean equal to the population parameter): (Proportion, Mean, Variance)

38
Q

Subjective Probability

A

P(A) estimated by using knowledge of relevant circumstances

39
Q

Range Rule of Thumb for Standard Deviation

A

s = range/4

40
Q

Outcome

A

specific event (HTH, HHT, etc.)