Quantitative Methods - Statistics Flashcards

(42 cards)

1
Q

What is the floor with being a decision maker?

A

In nearly all instances, there is information asymmetry.

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2
Q

What is probability theory?

A

Probability theory allows decision makers to assess risks and benefits associated with different decisions.

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3
Q

What is inference?

A

A conclusion based on evidence,

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4
Q

What is statistical inference?

A

The drawing of conclusions from a sample of data.

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5
Q

What is the frequentist view?

A

The proportion of trials in which the event occurs, calculated as if the number of trials approaches infinity.

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6
Q

What is the subjective view?

A

Someone’s degree of belief about the likelihood of an event occurring.

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7
Q

How would you work out the probability of head that come up on the toss of the coin? *as the number of trials approaches infinity.

A

Pr(H) = Number of heads/ number of trials.

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8
Q

What is empirical evidence?

A

Derived from or guided by experience or experiment.

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9
Q

What is an experiment?

A

An activity such as tossing a coin, which has a range of possible outcomes or events.

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10
Q

What is a trial?

A

A single performance of an experiment?

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11
Q

What is the sample space?

A

All possible outcomes of an experiment.

For tossing a coin, the sample space would be {heads, tails}.

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12
Q

What are the two different types of statistics>

A

Descriptive and inferential.

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13
Q

What is descriptive statistics?

A

Summarises a mass of information. E.g. Bar charts and pie charts.
We can use graphical and/or numerical methods. e.g. averages and standard deviations

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14
Q

What is inferential statistics?

A

Methods used to make estimates and predictions about a population on the basis of a sample taken from the population.

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15
Q

What is the difference between population and sample with respect to statistics?

A

Population include the whole group of interest whilst sample included only part of the whole group.

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16
Q

What is the purpose of descriptive statistics?

A

To present information in a clear, concise and accurate manner.

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17
Q

What are the key attributes of quantitative measures?

A
  1. Numerical
  2. Can be measured
  3. Can be ordered
18
Q

What are the key attributes of qualitative measures?

A
  1. Nonnumerical
  2. Categorical
  3. Describe quality of something.
19
Q

What are the three different levels of measurement?

A
  1. Nominal level data.
  2. Ordinal level data.
  3. Ratio level data.
20
Q

What is nominal data?

A

Only classified and counted.

21
Q

What is ordinal data?

A

Classified, counted, but order matter.

22
Q

What is ratio level data?

A

Ratios have meanings, zero means absence of chahracteristics.

23
Q

What is the general rule of thumb for knowing how many class intervals there should be on a frequency table?

A

The square root of the number of observations.

24
Q

Formula for frequency density of a histogram?

A

Frequency density =

Frequency/ Class width

25
Describe the frequency density.
Measures the frequency per unit of class width. This allows direct comparison between different class intervals.
26
What is the relative frequency?
Shows the proportion of observations that fall into each class interval.
27
What is the relative frequency formula?
Relative frequency = Frequency / Sum of Frequencies Should be a percentage.
28
What are the three numerical measures for graphs?
1. Location 2. Dispersion 3. Skewness.
29
What are the four measures of dispersion?
1. Range 2. Inter-Quartile 3. Variance 4. Standard Deviation
30
What is the variance? (formula in words)
The average of all squared deviations from the mean. Remember to square root the variance at the end though.
31
What values signify greater and lesser dispersion for variance?
The larger the variance value, the greater the dispersion of the observations.
32
Can you remember the sample variance (population variance)?
Well? Week 3 QMS...
33
What is the coefficient of variation?
Variation / Mean. Its a measure of relative dispersion and doesn't depend on the units.
34
What is the link between probability and statistical inference?
Probability underlies statistical inference.
35
What is probability theory?
Allows both mangers to assess risks and benefits associated with different decisions.
36
What is a compound event?
The probability that more than one event happen.
37
What is another name for a mutually exclusive event?
A disjoint event.
38
If two events are indecent, how is their probability worked out?
P(AnB) = P(A) + P(B)
39
What is an independent event?
When one event doesn't affect the outcome of another event.
40
What is a permutation?
A permutation is any arrangement of r objects selected from n possible options.
41
What is significant about permutations?
Order matters!
42
What are posterior probabilities?
The statistical probability that a hypothesis is true calculated in the light of relevant observations. e.g. Probability that its Box A or B given that is a Red ball.