Displaying Data, Stats and Errors Flashcards

understand how data can be displayed

1
Q

What are the three main ways of collecting data?

A
  • Polls
  • Experiments
  • Observational studies
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2
Q

What is a sample?

A

A subset of the target population

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3
Q

What are the benefits of Random sampling ?

A
  • Ensures equal chance of an individual being chosen from the Target population for sampling
  • Avoids Bias
  • Allows for the calculations of the likely size of sampling errors
  • Increasing the sample size, decreases sampling error
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4
Q

Describe precision

A

-Implies that the value of the statistic is similar in all samples

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5
Q

Describe Bias

A

-Implies that the sample statistic differs systematically

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6
Q

Describe the process of systematic random sampling with a random start

A
  • Take the size of the population (n) and the size of the sample (N)
  • Calculate the fixed period interval (K=N/n)
  • Randomly pick a number between 1 and K
  • sample the next individual and the next (individual + K) and so on
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7
Q

The process of splitting a sample into groups or subsets and then sampling is called…

A

Stratified Random sampling

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8
Q

Name the 8 types of non-sampling errors

A
  • Selection Bias
  • Self-selection Bias
  • Interviewer effects
  • Non-response Bias
  • Question effects
  • Survey format/conduction
  • Behavioural considerations
  • Transferring Findings
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9
Q

What is the term for taking a group in an experiment and splitting them up (By age for example)?

A

Blocking of experimental units

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10
Q

What are the two types of observational studies?

A
  • Prospective (for future events)

- Retrospective (for past events)

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11
Q

Why might you use a observational study?

A

If it is impossible, unethical or impractical to conduct an experiment

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12
Q

What is a confounding variable?

A

A factor not accounted for that introduces a difference in outcomes

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13
Q

What are the three types of plot sampling?

A
  • Completely random sampling
  • Systematic grid, random sampling
  • Systematic grid, Systematic sampling with a random start
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14
Q

What are the descriptions of response and explanatory variables ?

A
  • Response–> variable we would like to predict

- Explanatory–>variable that helps us explain or predict the response variable

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15
Q

What are the two types of quantitative data variables?

A
  • Continuous (infinite number of possible values)

- Discrete (distinct values)

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16
Q

What are the two types of qualitative data variables?

A
  • Ordinal (non-numerical, relative values like good, bad)

- Nominal (distinct by name only like green or October)

17
Q

What is the interquartile range ?

A

The difference between the 75th quantile and the 25th quantile

18
Q

Describe Histograms

A
  • Data partitioned into Bins on the x axis

- Number of points in each bin on the Y axis

19
Q

Describe the shape of a histogram for the following cases:

  • Mean>Median
  • Mean
A
  • Right skewed
  • Left skewed
  • Symmetrical
20
Q

What are some of the possible ways to visually display data?

A
  • Histogram
  • Box plot
  • Violin plot
  • Quilt plot
  • Bar chart
  • Pie Chart
21
Q

What are the lines that extend out of a box plot?

A

Whiskers and they extend to 1.5 times the interquartile range

22
Q

Describe the Normal distribution

A
  • Bell shaped

- Defined by two parameters, mean and variance

23
Q

Describe what confidence intervals are used to represent

A

A confidence interval is used to represent a range of values we are either 95 or 99% confident that the true value for the mean or statistical value lies