2.8: Descriptive v Inferential Statistics Flashcards

1
Q

Descriptive Statistics

A

Techniques to organize and summarize data collected from a sample.

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2
Q

Sample Statistics

A

Numeric summaries of our sample

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3
Q

What are 3 examples of sample statistics?

A
  1. Central tendency measures
  2. Variability
  3. Pearson Correlation
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4
Q

What is the symbol for mean in a sample?

A

X-bar

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5
Q

What is the symbol for variance in a sample?

A

s^2

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6
Q

What is the symbol for standard deviation in a sample?

A

s

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7
Q

What is the symbol for Sum of Squares in a sample?

A

SS

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8
Q

What is the symbol for correlation in a sample?

A

r

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9
Q

What is the symbol for z score in a sample?

A

z

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10
Q

What are two measures that can be conducted for samples but not population?

A
  1. Sum of squares (SS)
  2. Z Score
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11
Q

What can you use descriptive statistics for?

A

To analyze a sample by first calculating the mean and standard deviation

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12
Q

Point Estimate

A

A single estimate of a population value based on data from a sample.

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13
Q

What are 3 point estimate measurements?

A
  1. Frequency
  2. Central tendencies
  3. Pearson Correlation
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14
Q

Inferential statistics

A

Techniques based on probability to make conclusions about the population based on data from a sample.

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15
Q

What does inferential statistics give us?

A

More information about the population from a standard sample.

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16
Q

Population Parameters

A

Numeric summaries of our entire population (UNKNOWN)

17
Q

Population

A

Entire set of things we want to understand

18
Q

Inference

A

The process of drawing conclusions about population parameters based on a sample taken from the population

19
Q

What is the symbol for mean in a population?

20
Q

What is the symbol for variance in a population?

A

𝝈 (sigma squared)

21
Q

What is the symbol for standard deviation in a population?

A

𝝈(sigma)

22
Q

What is the symbol for correlation in a population?

23
Q

Confidence Interval (CI)

A

A range of how precise our point estimate is by capturing a range that VERY OFTEN contains the true population value

24
Q

What does a 95% confidence interval mean?

A

It contains the true population mean 95% of the time.

25
How do you state an analysis of a 95% confidence interval?
“If we ran a confidence interval 95% of the time, then 95% of that time the range would contain the true mean of the population.”
26
What happens to our confidence on margin of error as sample size increases?
Our level of confidence increases
27
What happens when the confidence interval overlaps with 0?
No relationship can be determined between the variables
28
What are two factors that affect precision/
1. Sample size 2. Variability level
29
How does sample size lead to more precise estimates?
The larger the sample size, the higher the precision
30
How does variability lead to more precise estimates?
Lower variability leads to higher precision
31
When can we not obtain detailed measurements?
When there is only inferred statistical values (not precise)
32
What adjustment is needed for an accurate population estimate?
degrees of freedom