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Advanced Data Analysis > Unit 2 > Flashcards

Unit 2 Flashcards

1
Q

What is the shorthand for null hypothesis?

A

H0

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2
Q

What is the shorthand for the alternate hypothesis?

A

H1

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3
Q

What are the two ways that variables can be defined?

A

-Dependent
-Independent

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4
Q

What is the definition of dependent variables?

A

-The property that is measured based on the original observation

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5
Q

What is the definition of independent variables?

A

Explanatory or factors that are in the model / experiment

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6
Q

What is quantitative data called in SPSS?

A

Scale

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7
Q

What is continuous data called in SPSS?

A

Ratio

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8
Q

Describe continuous data.

A

Infinite number of values between two points.

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9
Q

What is an example of continuous data?

A

-Length
-Weight

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10
Q

Describe discontinuous data.

A

-Can also be called meristic
-Is observations that exist on a limited number of values

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11
Q

What is an example of discrete data?

A

-Number of teeth
-Number of spots

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12
Q

What are examples of categorical variables?

A

-Ranked or ordinal
-Nominal or non-ordinal
-Binary

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13
Q

Describe ranked / ordinal data.

A

Data that a has rank
ie. Stress levels, where 0 is no stress and 5 is extremely stressed
-Maturity

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14
Q

Describe nominal / non-ordinal data

A

-Names
-Varieties
ie. Lough Derg

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15
Q

Describe binary data.

A

-A type of nominal data
-Yes / no
-Male / female

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16
Q

What are the variable types in SPSS?

A

-Numeric
-String

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17
Q

What are examples of numeric data in SPSS?

A

-Numbers
-Date
-Time

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18
Q

What are examples of scale quantitative data in SPSS?

A

-Interval
-No fixed origin of fixed distance (temperature)
-Ratio
-Fixed origin, fixed distance
(Age yrs) (Length cm)

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19
Q

What are parametric statistics?

A

-Makes assumptions about the distribution of the data
-Data needs to follow a normal distribution
-Very powerful to detect Type 1 errors

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20
Q

What are non-parametric statistics?

A

-Does not make assumptions
-Data transformed into ranks
-No distribution
-Less powerful, more conservation

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21
Q

What are the two types of errors in statistics?

A

-Type 1
-Type 2

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22
Q

What is a type 1 error?

A

Is a false positive
-Is when a null hypothesis is rejected when it should have been accepted

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23
Q

What is a type 2 error?

A

Is a false negative
Is when a null hypothesis is accepted when it should have been rejected

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24
Q

What is the central tendency?

A
  • Is a value that attempts to describe a set of data by identifying the central position within the data set
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25
Q

What are the most common measures of central tendency?

A

-The mean
-The median
-The mode

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26
Q

What is the ideal sample size for the best results when using the Central Limit theorem?

A

Samples sizes between 30 - 50
-Each sample must be an independent series of random observations
-All sampled from the same population

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27
Q

What is the central limit theorem?

A

Is that the distribution of sample means from a series of a large number of samples taken from the same population follows a normal distribution.

-Simplified to
The distribution of the sample’s means has an overall mean which is equal to the actual population mean

28
Q

When the variable is nominal, what is the best measure of central tendency?

A

-Use the mode

29
Q

When the variable is ordinal, what is the best measure of central tendency?

A

-Use the median

30
Q

When the variable is interval/ratio and not skewed, what is the best measure of central tendency?

A

-Use the mean

31
Q

When the variable is interval / ratio and is skewed, what is the best measure of central tendency?

A

-Use the median

32
Q

What are measures of variability?

A

-Numbers that describe the diversity or dispersion in the distribution of a variable

33
Q

What are the common measures of variation?

A

-Range
-Interquartile range

34
Q

Describe the range

A

-Crude measure of variability
-Minimum and maximum values
-Good at determining data entry errors

35
Q

Describe the interquartile range

A

-Uses medians (Boxplots)
-1st quartile
-2nd quartile
-3rd quartile

36
Q

How much data lies in the 1st quartile?

A

First 25% of values

37
Q

How much data lies in the 2nd quartile?

A

Contains the median
-50%
-Half the values

38
Q

How much data lies within the 3rd quartile?

A

-Also called the upper quartile
-75%

39
Q

What does the sum of squares represent?

A

-Represents a measure of deviation from the mean

40
Q

What is variance?

A

Is a measure of average variation

41
Q

What does SS stand for?

A

Sum of squares

42
Q

What does S^2 stand for?

A

Variance

43
Q

What does S stand for?

A

Standard deviation

44
Q

What is standard deviation?

A

Is the squared root of variance (S^2)

45
Q

What does SEOM stand for?

A

Standard error of the mean

46
Q

What does CV stand for?

A

Coefficient of variation

47
Q

What is the coefficient of variation?

A

-Is a percentage ratio
-Has no units
-Measure of relative variation

48
Q

How is the coefficient of variation calculated?

A

Standard deviation / mean *100

49
Q

What does a large confidence interval indicate?

A

-Larger uncertainty

50
Q

What are confidence intervals?

A

-If a sample from a population is very large, the true mean of the population has 95% probability of lying within 1.96 * SE

51
Q

What does SE stand for?

A

Standard error of the mean

52
Q

What happens to variance the larger a sample population is?

A

-The variance becomes smaller

53
Q

What are two tests for normality?

A

-Shapiro-Wilk
-Kolmogorov-Smirnov

54
Q

What normality test is more suited for sample sizes less than 50?

A

Shapiro- Wilk

55
Q

What is skewness?

A

-Is the degree of symmetry of a distribution around its mean.
-Mean is affected by skewness

56
Q

What is positive skewness?

A

Where the tail extends to positive values

57
Q

What is negative skewness?

A

Asymmetric tail that extends towards more negative values

58
Q

What is kurtosis?

A

Is the relative peak or flatness of a distribution compared with the normal distribution

59
Q

What does mesokurtic mean?

A

Normal

60
Q

What does leptokurtic mean?

A

-Positive
-Narrow distribution of values
-More observations closer to the mean

61
Q

What does platykurtic mean?

A

-Negative
-Wide distribution of values
-High dispersion

62
Q

When do you reject the null hypothesis?

A

If the test statistic is less than 0.05

63
Q

What does Levene’s t-test test for?

A

-Used to test for homogeneity of variances

64
Q

What are equal variances required for?

A

-Is required to perform t-tests and ANOVAs

65
Q

What ways can you transform data in SPSS?

A

-SQRT
-Log
-Arcsin

Advanced Data Analysis (5 decks)

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