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Business Stats - Exam 1 Terminology > Definitions > Flashcards

Definitions Flashcards

1
Q

One categorical variable use what type of graph?

A

pie chart, bar chart

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2
Q

Two categorical variables = what type of graph?

A

contingency table

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3
Q

Categorical Data

A

words and categories

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4
Q

Quantitative Data

A

numbers

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5
Q

Graphs for 1 Quantitative Variable

A

histograms, dot plots, stem and leaf plots, box plot

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6
Q

Graph for 2 Quantitative Variables

A

Scatterplot

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7
Q

Graph for 1 Quantitative Variable w/ multiple categories

A

Boxplots

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8
Q

Standard deviation is the

A

square root of the variance

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9
Q

Find Mean & Standard Deviation in JMP by:

A

> Analyze

>Distribution

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10
Q

Sample Statistic for one proportion

A

phat

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11
Q

Sample Statistic for one mean

A

ybar

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12
Q

Population Parameter for one proportion

A

p

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13
Q

Population Parameter for one mean

A

mu

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14
Q

Sample Statistic for 2 independent means

A

ybar1 - ybar2

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15
Q

Sample Statistic for matched pairs

A

ybard

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16
Q

Sample Statistic for 2 independent proportions

A

phat1 - phat2

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17
Q

Population Parameter for 2 independent means

A

mu1 - mu2

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18
Q

Population Parameter for matched pairs

A

mud

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19
Q

Matched Pairs example

A

twins, husbands & wives, pretest/posttest, sales vs no sales from SAME store

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20
Q

If you see average then…..

A

MEAN

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21
Q

If you see proportion then…..

A

PROPORTION

22
Q

Standard error =

A

the standard deviation of the SAMPLE

23
Q

For Means to be NORMAL:

A
  • large enough sample size
  • random
  • independent
  • not larger than 10% of population
24
Q

For Proportions to be NORMAL:

A
  • need at least 10 successes and 10 failures
  • random
  • independent
  • not larger than 10% of population
25
Q

Mean/Proportion problem, finding probability: first find standard error (std. deviation of the sample mean) then JMP =

A

> Distribution Calculator

26
Q

Width of a CI =

A

2(ME) OR (Upper CI - Lower CI)

27
Q

As confidence level increases, the width of the confidence level will

A

increase

28
Q

If sample size increases, width of the confidence interval will

A

decrease

29
Q

IF null hypothesis is contained within the confidence interval and when null is zero and contained you would

A

FAIL TO REJECT HO

30
Q

IF null hypothesis is NOT contained within the confidence interval or when null is zero and not contained you would

A

REJECT HO

31
Q

P-value tells us the probability of

A

obtaining the sample assuming the null hypothesis is true

32
Q

P-value lower than a (significance level)?

A

REJECT THAT HO
Results are statistically significant
There is sufficient evidence for HA

33
Q

P-val less than 0.01

A

VERY STRONG

34
Q

P-val less than 0.05

A

STRONG

35
Q

P-val greater than 0.10

A

NONE

36
Q

To determine where equal variances or not =

A

larger std dev / smaller std dev < 2 then ITS EQUAL/POOLED

37
Q

Ho and Ha are always with the

A

PARAMETERS

38
Q

Means use __ score

A

T

39
Q

Proportions use __ score

A

Z

40
Q

To find the CI of 2 proportions/means…

A

Use Hypothesis Test!!!

41
Q

Previous / expected in a study is the

A

p for the Ho and Ha

42
Q

You get a test statistic then what conclusion?

A

JMP: Dist calculator, input values to calculate probability, put test statistic as value, 2 sided, find p-val and make conclusion

43
Q

Type 1 & 2 Errors!!!

A

1 - Ho True - Reject - Alpha

2 - Ho False - FTR - Beta

44
Q

Increase alpha = increase probability of Type 1 means Type 2 will

A

DECREASE

45
Q

Increasing sample size will decrease probability of a ___ error

A

Type 2

46
Q

Power is

A

ability of a hypothesis test to detect the Ho is false

47
Q

The bigger the effect side, the easier to

A

reject Ho

48
Q

Chi Sq GOODNESS OF FIT

A

determine if data fits a given distribution
one categorical variable
whole what night people go out more problem

49
Q

Chi Sq INDEPENDENCE

A

determine if two categorical variables are independent

if 3X3 then it must be independence

50
Q

Chi Sq HOMOGENEITY

A

ONE categorical but over TWO populations

first semester, last semester problem testing crammed stuff

51
Q

Linear regression is always ___

A

EXPECTED

52
Q

residual - e =

A

actual (y) - predicted (yhat)

Business Stats - Exam 1 Terminology (2 decks)

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