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1
Q

Who first suggested the mathematical approach for determining the magnitude of a linear relationship between two variables, such as X and Y?

A

Francis Galton

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2
Q

In a simple linear relationship, when y is equal to the intercept, what will be the X value?

A

0

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3
Q

The r value should always be within which range?

A

Between -1 and 1

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4
Q

If you have data on people’s sex, age, the type of house they live in, whether or not they have type 2 diabetes, and their income, which analysis could you use to predict their income level from all the other variables?

A

Multiple regression

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5
Q

Analysis of variance (ANOVA) is a statistical method of comparing two or more sample ______

A

Means

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6
Q

What test is typically used to check for differences between individual groups or variable levels after finding a significant effect in an ANOVA?

A

Post hoc

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7
Q

Two new drugs are given, one to each of two groups. To test for the effect of the drugs on sleeping time and sleep quality over three time points, which ANOVA would be appropriate?

A

Repeated measures ANOVA

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8
Q

In the results of an ANOVA, what range of values can the F statistic be?

A

Between 0 and infinity

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9
Q

What are the 4 types of ‘potential for harm?’

A

Psychological harm, social harm, physical harm and legal harm

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10
Q

What is qualitative data?

A

Experiences, perceptions, described in words

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11
Q

What is quantitative data?

A

Numerical data, measured in numbers, data and/or hypothesis

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12
Q

What are some example methods of qualitative data?

A

Semi-structured interviews, focus groups, narrative reviews

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13
Q

Advantages of qualitative data?

A

Provides understanding, hear and understand participants voices

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14
Q

Disadvantages of qualitative data?

A

Small samples, time-intensive, researcher training

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15
Q

Example methods of quantitative data?

A

Surveys/questionnaires, randomised control trials, systematic review, meta-analysis

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16
Q

Advantages of quantitative data?

A

Limited variables, representative samples, statistical comparisons

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17
Q

Limitations of quantitative data?

A

Little understanding of individual experience, less contextual understanding

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18
Q

What is a population?

A

A complete set of objects/people

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19
Q

What is a sample?

A

A subset of a given population

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20
Q

What makes up a good sample?

A
  • Make sure sample reliably represents the population
  • Sample should not be modified once determined
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21
Q

What are variables?

A

A set of related events that can take on more than one value, in research it is something that can be changed such as a characteristic or value

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22
Q

What is an independent variable?

A

The IV is the the variable representing the value being changed or manipulated

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23
Q

What is an dependent variable?

A

The DV is the observed result of the IV being manipulated, it is something that (may) depend on the IV

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24
Q

What are control variables? (CVs)

A

Variables that are kept constant to prevent them influencing the effect of IV on DV

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25
Example of control variables
Example: Effect of drinking coffee on sleep quality: the control variables include - Time that the coffee was drunk, amount of coffee drunk, other activities during the evening etc.
26
What are the four representative data types in statistics?
Nominal (categorical) Ordinal Interval Ratio
27
What is nominal (categorical) data?
Cannot be ordered, cannot be counted Example: Country, gender, occupation
28
What is ordinal data?
Can be ordered, but cannot be added or subtracted Example: satisfaction rating, education level, spicy level
29
What is interval data?
Can be ordered, and their difference can be measured, but you cannot compute a ratio between two exam mark values
30
What is ratio data?
Interval + can take ratio between two values Example: Distance and height
31
Out of the 4 representative data types, which are qualitative and which are quantitative?
- Nominal and ordinal variables are qualitative - Interval and ratio variables are quantitative
32
In Jamovi, what are the 4 representative types of data grouped into?
- Nominal and ordinal are named as categorical - Interval and ratio variables are grouped into continuous
33
When describing data what comes under central tendency?
Mode, Median, Mean
34
When describing data what comes under Shape?
Skewness, Kurtosis
35
When describing data what comes under outliers?
Method for detection
36
When describing data what comes under spread?
- Quantile, Quartile, Percentile - Variance and standard deviation (SD) - Z-score
37
What is the square root of variance called?
The standard deviation
38
What is standard deviation?
The standard distance from the mean
39
What is the Z-score?
The number of standard deviations a given data point lies above or below the mean
40
Formula for Z-score?
(Persons x - mean x of category) Divided by Standard deviation
41
What is the formula for the 3rd moment?
Sum of (Distance from mean)3 to each data point Divided by Number of data points
42
What is the formula for skewness?
3rd moment Divided by SD*3
43
What does kurtosis measure?
The sharpness (corresponds to the 4th moment)
44
What is the 4th moment formula?
Sum of (Distance from mean)4 to each data point Divided by Number of data points
45
What is the formula for Kurtosis?
4th moment Divided by SD*4
46
What are outliers?
Extreme values relative to the bulk of values in a data set
47
Two methods to detect outliers?
- Outlier if Z-score is more than 3 or less than -3 - Outlier if greater than 1.5 x IQR above the 3rd quartile, or smaller than 1.5 x IQR below the 2nd quartile
48
What does a box plot include?
- Location of quartiles - Range of data excluding outliers - Outlier detected by quartile
49
In mathematics what does (A|B) mean?
The probability of obtaining A on the condition of B
50
What is the formula for binomial Probability?
Bi (K|n,q) K = heads n = number of tosses q = probability of getting heads each toss
51
What is cumulative probability?
The probability that the value falls in a certain range
52
What is two-tailed cumulative probability?
If you want to check the probability that a data is deviated from the centre (mean), you need to take the cumulative probability at both ends.
53
What does the area under the graph in that range mean when dealing with a continuous distribution?
The probability
54
What is a normal distribution?
Binomial distributions have specific shapes overtime called a normal distribution
55
Who was the normal (Gaussian) distribution named after?
Carl Friedrich Gauss
56
Which two numbers are used to describe a normal distribution?
Mean, Standard Deviation
57
What is theoretical perspective?
How you, the researcher, view the world and the assumptions that you make about the nature of the world
58
What is Epistemology?
The assumptions you make about the best way of investigating the world and about reality.
59
What are positivists?
People who believe the best way to investigate the world is through objective methods, such as observations. Positivism fits within a realist ontology
60
What are social constructionists?
They believe that reality does not exist by itself. Instead, it is constructed and given meaning by people. Their focus is therefore on feelings, beliefs and thoughts
61
What are p-values?
Probabilities used to reject hypotheses
62
What is an alpha-level?
A threshold level for the P-value
63
What is a null hypothesis?
The null hypothesis (H0) is a hypothesis against the research question, claiming that there is no difference in the result and the only differences observed are just noise/error
64
Why do we always test the null hypothesis being true?
You can never prove something is true but can prove something is false
65
What are the two types of error in statistical tests?
Type 1 (false-positive) Type 2 (false-negative)
66
What is a type 1 (false-positive) error?
The vaccine is not effective but you conclude it is effective
67
What is a type 2 (false-negative) error?
The vaccine is effective but you conclude it is not effective
68
What are the three typical types of test when binomial testing?
- Observed proportion < expected proportion (cumulative probability from 0 to observed) - Observed proportion > expected proportion (1- cumulative probability from observed to max) - Observed proportion = expected proportion (Two-tailed cumulative probability, same distance from the mean)
69
What is the confidence interval?
A range of plausible values associated with a confidence level (usually 95%)
70
What is a binomial test?
A statistical test that concerns whether a proportion observed in your data is different from a known proportion
71
When do you reject the null hypothesis?
When the p-value is below the alpha-level
72
What test do you use when there are proportions with more than two levels?
Chi-square goodness-of-fit test
73
What test do you use when comparing proportions across two or more groups?
Chi-square test of association
74
What test do you use when comparing a measure with a fixed value?
One-sample t-test
75
What test do you use when comparing a measure across two groups?
Independent: two-samples t-test Paired: Paired t-test
76
What are the two types of Chi-square (x*2) tests?
Goodness-of-fit Test of association
77
What is the chi goodness-of-fit test?
Used to determine whether a variable is likely to come from a specified distribution or not
78
What is the Chi test of association (or test of independence) test?
How proportions of two data sets are associated
79
What is Benford’s law?
The frequency of first digits of naturally occurring numerical data follow the known proportion
80
What is the paired samples - Mcnemar’s test?
Data points are paired across two groups
81
What is a one sample t-test?
Compared the mean of one sample group against a fixed value
82
What is an independent samples t-test?
Compares the observed difference between the means of two independent samples or categories
83
What is the central limit theorem?
Sampling distribution of the mean is normal - if you take groups of n - samples from the distribution and calculate the means of each sample group, those means are normally distributed. This holds when the sample size n is sufficiently large.
84
What are parametric tests?
Statistical tests based on the normality assumption
85
How can test of normality be tested?
Shapiro-wilk test
86
How can you test equality of variance?
Levene’s test of equal variance
87
What are the significance of difference in variance reported as?
P-value
88
When is the variance not equal/equal in reference to the P- value?
P<0.05: variance not equal P>0.05: variance are equal
89
If variances are not equal which test should you use?
Welch’s t-test
90
What does correlation do?
Finds the ‘best fit’ line by minimising the differences between the data and the line
91
Correlation formula?
R = How much X and Y change together Divided by How much X and Y change separately
92
How do you know if correlation is positive or negative?
If r is above zero, your correlation is positive If r is below zero your correlation is negative
93
How strong is your correlation?
If r is close to one, your correlation is strong If r is close to zero, your correlation is weak
94
What does the R*2 value tell you?
How much of the variance is explained by your correlation If r*2 is close to one, your correlation explains a lot of variance If r*2 is close to zero, your correlation explains only a little variance
95
In reference to regression and y=mx + c when, x increases by 1 what does y increase by?
The slope
96
What is different about regression compared to correlation?
- Can describe multiple relationships - X and Y not inter-changeable - Allows prediction
97
What are the main points about multiple regression compared to simple regression?
- A single outcome variable (y) - Multiple predictor variables (x1, x2, x3)
98
What does regression give you?
Strength, direction and equations of relationships
99
What is the purpose of the general linear model (GLM)?
To access the strengths and directions of relationships and differences, strengths of interventions and manipulations
100
What are the different types of ANOVA?
- One-way ANOVA - Factorial (or multi-way) ANOVA - Repeated measures (or within-subjects) ANOVA - Mixed ANOVA
101
What are ANOVAs used for?
- Different conditions in a study - Different groups in a study
102
What is a one-way ANOVA?
Three or more groups; one outcome variable
103
What is Factorial (or multi-way) ANOVA?
Two or more groups; two or more categorical predictor variables; one outcome variable
104
What is repeated measures (or within-subjects) ANOVA?
One group: two or more categorical predictor variables; one outcome variable
105
What is Mixed ANOVA?
Two or more groups; one or more categorical predictor variables; one outcome variable
106
What are interactions in ANOVA results?
When differences in one variable is affected by differences in another variable

Research Methods MCQ (1 decks)

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