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Stats > Lecture 3 Chapter 3 > Flashcards

Lecture 3 Chapter 3 Flashcards

1
Q

What is the purpose of descriptive statistics?

A

Describe data only

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2
Q

What is the purpose of inferential statistics?

A

Determine likelihood of pure randomness explaining data

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3
Q

Name the three types of descriptive statitsics?

A

1) Measures of Central Tendency
2) Measures of Variability
3)Statistics for describing shapes of distributions

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4
Q

What are the three measures of central tendency?

A

Mean
Median
Mode

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5
Q

How to choose the right measure of central tendency?

A

-The type of measure of central tendency you choose depends on the level of measurement of the variable
-Measures of central tendency are linked to the levels of measurement of variables

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6
Q

What is the mode?

A

The value that occurs most frequently in a set of data

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7
Q

A distribution with two highest frequently occurring values is called ?

A

Bimodal

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8
Q

A distribution with three or more highest frequently occurring values is called ?

A

multimodal

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9
Q

What type of data is the best for the mode?

A

Nominal

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10
Q

Why in nominal data data best for mode?

A

With nominal and dichotomous data, we cannot rank the values, but can only count them

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11
Q

What is the median?

A

The middle value/score in a sorted set of data (in ascending or descending order)

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12
Q

How do you get the median?

A

Half of the scores fall above the median, and half fall below the median; it’s the center score

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13
Q

What type of data is best for the median?

A

Ordinal

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14
Q

Why does median not work for nominal data?

A

-Doesn’t work for nominal data because you can’t order the categories
-So we can’t say half of nominal categories are “less than” and half are “greater than” a particular category

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15
Q

What is the mean?

A

The arithmetic average

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16
Q

What is the data is best for the mean?

A

Normal

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17
Q

What is a weakness to the mean?

A

-A single very large (or small) number can dramatically change the mean
-The mean can be greatly influenced/swayed by outliers (scores far higher or lower than most)

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18
Q

What is a strength of the mean?

A

-The mean best describes the center of the values of a variable
-The mean provides a good representation of the entire data for a variable

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19
Q

What does it mean when data is normally distributed?

A

meaning no outliers or numbers are close to each other

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20
Q

How can you tell data is normally distributed?

A

the mean median, and mode can have the same value

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21
Q

what is the purpose of measures of variability?

A

-Describe how the values of a variable are spread out or dispersed
-Describe how much the values vary from each other

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22
Q

What are the three measures of variability?

A
  • Number of categories
  • Range
  • Standard deviation
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23
Q

How do you choose the best measure of variability?

A
  • Best to use depends on the level of measurement of the variable or type of data you have
24
Q

What is the measure of variability for nominal data?

A

How many categories

25
Q

What is the measure of variability for dichotomous data?

A

Range is always 1
how many categories is always 2

26
Q

What is the measure of variability for ordinal data?

A

Range & Interquartile Range
but range is preferred

27
Q

What is the measure of variability for normal/scale data?

A

Standard Deviation

28
Q

What is the definition of standard deviation?

A

Is the “average distance” between each score and the mean

29
Q

What does standard deviation tell us?

A

Tells you how far the values are spread out around the mean of the variable

30
Q

What does a higher standard deviation mean?

A
  • The higher the standard deviation, the higher the “average distance” between each score and the mean
  • The higher the standard deviation, the more spread out about the mean are the individual scores in the data set
31
Q

What does a lower standard deviation mean?

A

The average distance is smaller, meaning the scores are closer together

32
Q

The mean and standard deviation can be used to calculate

A

“standardized scores”

33
Q

What is another name for what the mean and standard deviation calculate

A

Z-Score

34
Q

What does the z-score mean

A

-Z-scores tell you the number of standard deviations a score/value is from the mean
-Z-scores are expressed in terms of standard deviations from their means

35
Q

What is the mean and standard deviation in a z-score?

A

Z-scores have a mean of 0 and a standard deviation of 1

36
Q

Why is the z-score important?

A

-Used to compare two or more values that are part of different distributions
* Useful for comparing different groups because scores are standardized

37
Q

What is the calculation for the z score?

A

Raw score - group mean / divided by the group standard deviation

38
Q

What is the definition of normal distribution?

A

A theoretical distribution that provides a reference point for describing the shape of a distribution

39
Q

How can we find the percentage of scores that are below or above a particular score on the normal curve?

A

We use the z-score calculation

40
Q

what do Negative z-score tells us?

A

the actual raw score is below the mean

41
Q

What does a Positive z-score tells us ?

A

the actual raw score is above the mean

42
Q

What percent of the stores fall within 1 positive/ 1 negative standard deviation?

A

About 68% fall within +/- 1 SD from the Mean

43
Q

What percent of the stores fall within 2 positive/ 2 negative standard deviation?

A

About 95% fall within +/- 2 SD from the Mean

44
Q

What percent of the scores fall within 3 positive/ 3 negative standard deviations?

A

About 99% fall within +/- 3 SD from the Mean

45
Q

By knowing how much area is between plus and minus 1 sd what does this help us do?

A

helps us to describe the spread of values of a normally distributed variable

46
Q

What is the central limit theorem?

A

Tells us that data are often distributed approximately as the normal curve when the sample size is large

47
Q

What is skewness?

A

*Tells us how symmetrical a distribution is
* Describes data symmetry
*Describes how the shape of a distribution of scores differ from the normal curve

48
Q

If the data is symmetrical does it have a skewness?

A

No skewness

49
Q

How do we determine the type of skewness of a distribution?

A

Comparing the mean, median and mode
The type of skewness of a distribution is determined by the direction that the tail trails off

50
Q

What is positive skewness?

A

The tail trails off to the right

51
Q

Where are the mean, median and mode in positive skewness?

A

The mean is higher than the median, which is also higher than the mode

52
Q

What is negative skewness?

A

The tail trails off to the left

53
Q

Where are the mean, median and mode in negative skewness?

A

The mean is lower than the median, which is also lower than the mode

54
Q

What data is assumed to be skewed?

A

Nominal and ordinal

55
Q

Many statistical tests may only be used if the data is _______?

A

normally distributed variables or data

56
Q

How do we tell if scale/normal data are normally distributed?

A

-Use skewness: The mean, median, and mode must be equal (or very close) to be normally distributed
* Create a histogram (with the normal curve superimposed) and compare it to the normal curve

Stats (8 decks)

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