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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
What are the most common measures of central tendency?
-The mean -The median -The mode
26
What is the ideal sample size for the best results when using the Central Limit theorem?
Samples sizes between 30 - 50 -Each sample must be an independent series of random observations -All sampled from the same population
27
What is the central limit theorem?
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
When the variable is nominal, what is the best measure of central tendency?
-Use the mode
29
When the variable is ordinal, what is the best measure of central tendency?
-Use the median
30
When the variable is interval/ratio and not skewed, what is the best measure of central tendency?
-Use the mean
31
When the variable is interval / ratio and is skewed, what is the best measure of central tendency?
-Use the median
32
What are measures of variability?
-Numbers that describe the diversity or dispersion in the distribution of a variable
33
What are the common measures of variation?
-Range -Interquartile range
34
Describe the range
-Crude measure of variability -Minimum and maximum values -Good at determining data entry errors
35
Describe the interquartile range
-Uses medians (Boxplots) -1st quartile -2nd quartile -3rd quartile
36
How much data lies in the 1st quartile?
First 25% of values
37
How much data lies in the 2nd quartile?
Contains the median -50% -Half the values
38
How much data lies within the 3rd quartile?
-Also called the upper quartile -75%
39
What does the sum of squares represent?
-Represents a measure of deviation from the mean
40
What is variance?
Is a measure of average variation
41
What does SS stand for?
Sum of squares
42
What does S^2 stand for?
Variance
43
What does S stand for?
Standard deviation
44
What is standard deviation?
Is the squared root of variance (S^2)
45
What does SEOM stand for?
Standard error of the mean
46
What does CV stand for?
Coefficient of variation
47
What is the coefficient of variation?
-Is a percentage ratio -Has no units -Measure of relative variation
48
How is the coefficient of variation calculated?
Standard deviation / mean *100
49
What does a large confidence interval indicate?
-Larger uncertainty
50
What are confidence intervals?
-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
What does SE stand for?
Standard error of the mean
52
What happens to variance the larger a sample population is?
-The variance becomes smaller
53
What are two tests for normality?
-Shapiro-Wilk -Kolmogorov-Smirnov
54
What normality test is more suited for sample sizes less than 50?
Shapiro- Wilk
55
What is skewness?
-Is the degree of symmetry of a distribution around its mean. -Mean is affected by skewness
56
What is positive skewness?
Where the tail extends to positive values
57
What is negative skewness?
Asymmetric tail that extends towards more negative values
58
What is kurtosis?
Is the relative peak or flatness of a distribution compared with the normal distribution
59
What does mesokurtic mean?
Normal
60
What does leptokurtic mean?
-Positive -Narrow distribution of values -More observations closer to the mean
61
What does platykurtic mean?
-Negative -Wide distribution of values -High dispersion
62
When do you reject the null hypothesis?
If the test statistic is less than 0.05
63
What does Levene's t-test test for?
-Used to test for homogeneity of variances
64
What are equal variances required for?
-Is required to perform t-tests and ANOVAs
65
What ways can you transform data in SPSS?
-SQRT -Log -Arcsin

Advanced Data Analysis (5 decks)

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