Class 8, 9 Spring ᯓᑣ𐭩 Flashcards

1
Q

What is joint probability?

A

The probability of getting the variables/processes/outcomes A or B

β€˜Or’ means and/or.

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2
Q

What is the probability for independent variables A and B?

A

The probability for events from independent variables/processes/outcomes A and B.

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3
Q

What is the probability for dependent variables A and B?

A

The probability of outcome A, given knowledge about B.

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4
Q

What percentage of people like In-N-Out best?

A

68% of people like In-N-Out best.

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5
Q

What is the percentage of women who prefer In-N-Out?

A

72% of women prefer In-N-Out.

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6
Q

What is the percentage of men who prefer In-N-Out?

A

65% of men prefer In-N-Out.

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7
Q

What are descriptive statistics?

A

Methods used to summarize or describe observations in a particular sample.

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8
Q

What are inferential statistics?

A

Using observations as a basis for making estimates or predictions about a situation that has not yet been observed.

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9
Q

Give an example of descriptive statistics.

A

Calculating the average height of a whole classroom.

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10
Q

Give an example of inferential statistics.

A

Extrapolating the average height of one 5th grade class to predict another.

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11
Q

What is a population in statistics?

A

All the cases or situations that the statistician wants their inferences to apply to.

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12
Q

What is a sample?

A

A relatively small selection from within a population.

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13
Q

What is a simple random sample?

A

An approach where each element of the population is likely to be selected.

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14
Q

What does inferential statistics focus on?

A

Making estimates and inferences about a wider population.

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15
Q

What is random error?

A

Describes how much an estimate will tend to vary from one sample to the next.

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16
Q

What is the symbol for sample size?

17
Q

What is the symbol for population size?

18
Q

True or False: Random error has a preferred direction away from the mean.

19
Q

What is systematic bias?

A

The difference between survey results and population values due to incorrect measurements.

20
Q

What can cause measurement bias?

A

Incorrect measurements from broken tools or poorly trained assistants.

21
Q

What can cause sampling bias?

A

Not selecting a truly random sample representative of the larger population.

22
Q

What is the impact of random error on estimates?

A

It may be imprecise, but not inaccurate.

23
Q

What is the main way to reduce random error?

A

Collecting more data (increasing sample size).

24
Q

What is the paradox of sampling?

A

A sample is misleading unless it is representative of all natural variation in a population.

25
Q

What is a confidence interval?

A

A range of plausible values where we are likely to find the true population parameter.

26
Q

What conditions must be checked for constructing a confidence interval?

A

The sampling distribution must be normally distributed and unbiased.

27
Q

What is the central limit theorem?

A

A theorem that describes the conditions under which the sampling distribution of the sample mean will be normally distributed.

28
Q

What is a confidence interval (CI)?

A

A range of plausible values where we are likely to find the population parameter

A confidence interval represents uncertainty in estimates and accounts for random errors.

29
Q

What is the purpose of using confidence intervals?

A

To provide a plausible range of values for the population proportion instead of just a point estimate

This helps capture the true parameter more effectively.

30
Q

What does the sample proportion p-hat represent?

A

A single plausible value for the population proportion p

p-hat is derived from sample data and is subject to error.

31
Q

Why is using only a point estimate compared to fishing in a murky lake with a spear?

A

Because it has a high chance of missing the true population parameter

A point estimate does not account for variability or uncertainty.

32
Q

What is the analogy used to describe confidence intervals?

A

Fishing with a net

A net increases the chances of capturing fish, similar to how a CI increases the likelihood of capturing the true parameter.

33
Q

What must be ensured for a confidence interval to be constructed?

A

The sampling distribution must be normally distributed and unbiased

This is related to the conditions of the central limit theorem.

34
Q

What is the relationship between standard error and sample proportion?

A

The sample proportion has some standard error associated with it

Standard error quantifies the variability of the sample proportion as an estimate of the population proportion.

35
Q

Fill in the blank: A confidence interval is like fishing with a net, representing a range of _______.

A

[plausible values]

This analogy emphasizes the idea of capturing a range of potential outcomes.

36
Q

What theorem’s conditions need to be checked for confidence intervals?

A

Central Limit Theorem

This theorem ensures that the sampling distribution approaches normality as sample size increases.