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AP Statistics > Chapter 7 > Flashcards

Chapter 7 Flashcards

1
Q

Population parameter

A

Quantitative- M or Mx

Porportion/cat-P or π

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2
Q

Population Standard deviation

A

Quantitative- σ or σx

Porportion/cat-none

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3
Q

M

A

quant opulation parameter

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4
Q

Mx

A

Quant population parameter

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5
Q

P

A

Porportional/cat population parameter

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6
Q

π

A

Porportional/cat population parameter

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7
Q

Sample statisctic

A

Quantitative- x̅

Porportion- p̂

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8
Q

σ

A

Quant standard deviation of population

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9
Q

σx

A

Quant standard deviation of population

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10
Q

Sample standard deviation

A

Quantitative- Sx

Porportion/Categorical- None

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11
Q

x̅

A

Quantitative sample statistic

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12
Q

p̂

A

Porportion/cat sample statistic

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13
Q

Mean of the sampling distribution

A

Quantitative- Mx̅

Porportion/Categorical- Mp̂

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14
Q

Sx

A

Quant sample standard deviation

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15
Q

Standard deviation of the sampling distribution

A

Quantitative- σx̅

Porportion/Categorical- σp̂

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16
Q

Mx̅

A

Quant mean of the sampling distribution

17
Q

Mp̂

A

Porportion/cat mean of the sampling distribution

18
Q

σx̅

A

Quant standard deviation of the sampling distribution

19
Q

σp̂

A

Porportion/cat of standard deviation of the sampling distribution

20
Q

Sampling distribution for quantitative center

A

Mx̅= M if the sample was selected in a random unbiased manner

21
Q

Sampling distribution for porportion center

A

Mp̂= P if the sample was selected in a random unbiased manner

22
Q

Sampling distribution for quantitative shape

A

Shape of sampling distribution is appprox normal if the sample size is sufficently large enough to overcome skewness in the populaiton
n=30 is sufficently large
n=1 is sufficently large for nomral populations
More skew in population means you need an bigger sample size for it to be normal

23
Q

Sampling distribution for porportional shape

A

The sample size is sufficently large if:
np> or = 10
and
nq> or = 10

24
Q

Sampling distribution for quantitative shape

A

σx = σ / sqrt(n).

If the population is sufficently large and n < 1/10 population

25
Q

Sampling distribution for porporional shape

A

σp̂= Squart root(pq/n)

if the population is sufficently large and n < 1/10pop

26
Q

Sampling distribution

A

Distribution of all possible statistics (x bars and p hats) of a specific sample size taken from a specific popualtion

27
Q

Population distribution

A

Distribution of a variable of all individuals

28
Q

Central limit theorem

A

As the sample size of only a sampling distribution increases and sample size is sufficently large,

  1. The shape of the sampling distribution becomes more normal
  2. The mean of the sampling distribution stays exactly the same
  3. The standard deviation of the sampling distribution decreases
29
Q

How is the mean of a sampling distribution related to the true population mean for the distribution

A

It is exactly the same

30
Q

How is the standard deviation of the sampling distribution related to the standard deviation of the population

A

Sampling distribution standard deviation is less than the standard deviation of the population

31
Q

Will we ever know the true population parameters (like mean and standard deviation)

A

no

32
Q

Would it be necessary to collect a sample from the population if you already know the population parameters you were interested in

A

No

33
Q

How is our degree of confidence change in relation to the sample size of our sampling distribtion

A

If the sample size of the sampling distribution is larger, we are more confident in our estimate of the parameters due to the smaller standard deviation

34
Q

How will the center of a sampling distribution change as the sample size n increases

A

It doesnt

35
Q

How will the standard deviation of the sampling distribution change as the sample size increases

A

It decrease

36
Q

Why are bigger sample sizes better for sampling distributions

A

They provide less sampling distribution while remaining unbiased (mean of the sampling distribution is equal to the mean of the population)

AP Statistics (1 decks)

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