Vocab III Flashcards

1
Q

Do you use Z or T for proportions in hypothesis testing?

A

always use Z for proportions, we assume the proportion is normally distributed so to check use: n(p’) > 5 & n(1-p’) > 5

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2
Q

how do we find the critical value for proportion hypothesis testing?

A

go to the t-table and look for either the one-tail or two tail then go all the way down to the z

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3
Q

when do we use the F distribution?

A

the F distribution is used when comparing variances, not averages

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4
Q

how can one preform a F-testing?

A

-normally distributed
- independent of each other

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5
Q

what does this mean?

Ho: σ1^2 = σ2^2
Ha: σ1^2 ≠ σ2^2

A

either the population has equal variances or unequal variances

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6
Q

how do you find the other side for the F-distribution CV when the ?

A

we divide the cv (1/CV)

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7
Q

what is Poisson distribution?

A

is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space.

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8
Q

Poisson distribution symbols
e:
λ:
x:
!:

A

-is a constant(remains that symbol throughout solving)
-landa, historic average(number we are given)
-is the number of times we are interested on
-factorialy

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9
Q

is the mean of the sampling distribution ever going to be exactly the mean of the population?

A

NO

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10
Q

central limit theorem

A

is how we are able to make conclusions about a population, even if we do not know the true mean

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11
Q

type I error

A

occurs when you reject a good null hypothesis when it was true

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12
Q

type II error

A

occurs when you don’t reject the null hypothesis when it was false

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13
Q

hypothesis testing

A

the most important statistical test. involves collecting data from a sample and evaluating it. this is how a decision is made using the evidence

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14
Q

what is a sampling distribution

A

is a probability distribution of a statistic that is obtained through repeated sampling of a specific population

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15
Q

key words for Ha: when it is >

A

greater than
more than
bigger than

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16
Q

key words for Ho: when it is ≤

A

less than or equal to
is at most

17
Q

key words for Ha: when it is <

A

less than
fewer than
smaller than

18
Q

key words for Ho: when it is ≥

A

greater than or equal to
is at least

19
Q

key words for Ha: when it is ≠

A

not equal
differs
not the same as
is different than

20
Q

statistics

A

is the study of how to collect, organize, analyze, and interpret numerical information from data

21
Q

parameter statistics

A

is a numerical measure that describes an aspect of a population

22
Q

sample statistic

A

is a numerical measure that described an aspect of a sample

23
Q

descriptive statistic

A

involved methods of organizing, picturing, and summarizing info from samples of populations

24
Q

inferential statistics

A

involves methods of using information from a sample to draw conclusions regarding the population

25
Q

standard deviation

A

provides a measure of the overall variation in a data set
-will be small when the data are all concentrated close to the mean, showing little variation or spread
-will be larger when the data values are more spread out from the mean, showing more variation

26
Q

methods of assigning probabilities

A

classical, relative frequency, subjective

27
Q

rules for assigning probabilities

A

probability must be between 0 & 1
if all events are mutually exclusive (meaning an event can only be in one category total probabilities added up must = 1)

28
Q

sampling errors

A

non responsive bias
selection bias
halo effect
respondent error

29
Q

sample methods

A

simple random
judgement
quota
stratified random
convenience
cluster
systemic
snowball