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Stats > Midterm 1 > Flashcards

Midterm 1 Flashcards

1
Q

Statistics

A

science that involves the
-collection of data
- organization
- analyzing
- interpret

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2
Q

collection of data examples

A
  • interviews
  • questionaiires
  • calls
  • conducting experiments
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3
Q

organization of data examples

A
  • graphs
  • bar graph
  • histograms
  • scatter plots
  • dot plot
  • stem leaf plot
  • lowest to highest
  • five number summary
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4
Q

analyzing data means

A
  • to make conclusions
  • normal distribution
  • testing hypothesis
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5
Q

discrete data

A
  • finite numbers
  • whole numbers
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6
Q

continuous data

A
  • infinite
  • mixture of whole and decimals
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7
Q

qualitative data broken down into:

A

ordinal and nominal

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8
Q

nominal data

A
  • no organization to the order
  • religion, race, flavours
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9
Q

ordinal data

A
  • order, mathematical sense
  • order of grades: A, B, C, D
  • ranks (junior officer, senior officer)
  • flavours (how good they are)
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10
Q

interval data

A
  • quantitative broken down further
  • no natural zero, zero has no meaning
  • temperature
  • years
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11
Q

ratio data

A
  • quantitative broke down more
  • has natural zero
  • bank account
  • rental cars
  • time of zero for delivery
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12
Q

sampling

A

process of getting samples for analysis

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13
Q

statistic

A

characteristic of a sample

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14
Q

parameter

A

characteristic of a population

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15
Q

sampling methods

A

random
systematic
stratified
cluster
convinence

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16
Q

random sampling and advantage

A

put everything into basket and picking, no bias.
n must be equal or greater than 30.
- without replacement
- advantage- allows equal chances for all samples, not biased

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17
Q

systematic

A
  • order, every third for fourth person, pick randomly
  • selecting the kth item
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18
Q

stratified sampling and advantage

A
  • put the communities into similar characteristics (S, N, E, W)
  • those are statas
  • then you go to each strat and do random sampling
  • n will be properly represented
  • youre sure you will get north side representation
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19
Q

convinence sampling and disadvantage

A

pick samples ased on info that is already out there. take your sampling form the good side of town, etc
- biased

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20
Q

cluster sampling and disadvantage

A

similar to stratified
- put into clusters (just like stratas)
- but instead of random sampling, you pick everyone out of the clusters.
- there are so many people, ususally not the best method

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21
Q

descriptive stats

A
  • organizing and analyzing
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22
Q

inferential stats

A
  • conclusion
  • interpreting the data
  • testing hypothesis
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23
Q

Range

A
  • every set of data has a range
    = H-L
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24
Q

outliars

A

extreme values

25
Q

frequency table

A
  • class and frequency ONLY
  • all whole numbers
26
Q

how to get class width

A

= range / # of classes
- round to nearest whole #
- must include the lowest value

27
Q

frequency

A

how many times the data comes up on the chart

28
Q

frequency histogram

A
  • class, frequency and boundary
29
Q

boundary

A
  • continuous data (add or minus 0.5 to make it smooth)
30
Q

mode (frequency histogram)

A
  • each of the bars in the bar graph
31
Q

relative frequency table

A
  • percentage of the frequency
  • frequency divided by the total amount
  • class, frequency, relative frequency, boundary
32
Q

cummulative relative frequency

A
  • first frequency added to the second, then take that total and add to the third. then you divide by the total to make a percentage
  • increasing trend
  • will give you the total
  • table- class, frequency, relative frequency, cumm, cumm relative frequency
33
Q

mean

A

ΣXi (n on top, i=1 on bottom)

34
Q

median

A

M
- middle value
- (n+1)/2 th position

35
Q

mode

A

most occuring, highest frequency

36
Q

Mid range

A

H plus L / 2

37
Q

5 number summary

A

L, Q1, M, Q3, H

38
Q

Q1, Q3

A

from the median- (n+1)/2 th position

39
Q

Box plot

A

five number summary
- can have multiple boxes on the plot just number on the x axis
- horizontal or vertical

40
Q

Q2

A

Q3-Q1

41
Q

Standard deviation

A

(s)
- measure of how far your point is from the mean
- measures variation

= (square root) Σ[(x-xbar)]2 / n-1

42
Q

variants

A

s2
- standard deviation squared

43
Q

skewness

A

M, mode, mean
- normal, positive, negative

44
Q

stem leaf plot

A
  • no commas
  • start filling leafs from the stem
  • leaf can hold only one element, the last
  • give # room
45
Q

event P(A)

A

action of interest
- the A variable

46
Q

represent a probability how

A

percentage, decimal, fraction
- all probabilities should add up to 1

47
Q

independent events

A

the occurance of A does not depend on the occurance of B

48
Q

mutually exclusive event (disjoint)

A

events cannot happen at the same time

49
Q

mutually inclusive events (adjoint events)

A

can happen at the same time

50
Q

simple events

A

one experiment happens at a time and will have a single outcome (tossing a coin)

51
Q

compound events

A
  • the event has more than one outcome (rolling a dice)
52
Q

contingency table

A

compares two quantitative variables
- totals on both sides
- title

53
Q

P(AUB)

A
  • union
  • covering all percentages of A and B
54
Q

P(A∩B)

A
  • intersection
55
Q

conditional probability P(A/B)

A
  • given that
    =P(A∩B)/P(B)
  • events must be inclusive, have an intersection
  • something in common
56
Q

Discrete Probability characteristics

A

1) all the x values are whole #’s (discrete)
2) probabilities are positive and lie between 0 and 1
3) summation of probabilities is 1

57
Q

mean of a discrete probability

A

µx= ΣxiPi = xiPi + x2P2 …. xnPn

58
Q

variance of discrete probaility

A

σ2x = Σ(xi-µx)2 Pi

59
Q

standard deviation

A

square the variance

Stats (2 decks)

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