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AP0609 Component 1 > Statistics 1 > Flashcards

Statistics 1 Flashcards

1
Q

What is the definition of a population?

A

Every member with selected characteristics and sharing common property in a specific region

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2
Q

What is the definition of a sample?

A

A representative sub-set of a given population, unrelated and chosen at random

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3
Q

What is the difference between the response (dependent) variable and the explanatory (independent) variable?

A

The response (dependent variable is of interest in an experiment, it depends on another factor (independent/explanatory) variable to cause change.

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4
Q

What are the two sub-sets of qualitative data?

A

Nominal Data - categorical information that lacks inherent order or ranking

Ordinal Data - information with order or ranking, differences between values are not quantifiable e.g. survey responses or educational levels

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5
Q

What are the two sub-sets of quantitative data?

A

Discontinuous - obtained by counting integers

Continuous - (Most used) obtained by measurement e.g. height, BMI

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6
Q

What type of data is:
Number of carbon atoms in a molecule

A

Discontinuous quantitative

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7
Q

What type of data is:
Mass of a chemical compound weighed on a balance

A

Continuous quantitative

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8
Q

What type of data is:
Absorbance measured using a spectrophotometer

A

Continuous quantitative

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9
Q

What type of data is:
Gender of students in a class

A

Nominal Qualitative

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10
Q

What type of data is:
Educational levels of students in a class

A

Ordinal Qualitative

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11
Q

Define Accuracy

A

Closeness of measurements to the true value

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12
Q

Define precision

A

Closeness of repeated measurements to eachother

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13
Q

Define Data Set

A

Collection of information based on an experiment or research question, collected in term of observations and variables, ready to be processed, analyzed, distributed or shared.

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14
Q

Define descriptive statistics

A

Summarize a set of data values in terms of center and spread

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15
Q

What does average show?

A

The general tendency of the data

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16
Q

What distribution of data can you find the true mean?

A

Normally distributed data

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17
Q

Define variance

A

Average squared deviation from the mean

18
Q

Define Standard Deviation

A

Variability or spread of the data from the mean of the sample

19
Q

Define Standard Error

A

Deviation from the mean of the populations, this tends to be estimations used to calculate confidence

20
Q

What is the Confidence Interval?

A

What percentage confidence you are that if someone repeated the test with a different sample, you would get the same results

21
Q

Give the basic principles of coefficient of variance (CoV)

A
  • Larger the number the larger the spread
  • Normally expressed as a percentage of the mean
  • Useful for comparisons of 2 data sets in different units
22
Q

Give the formula for Coefficient of variance (CoV)

A

CoV = (SD/mean)*100

23
Q

Define H0

A

The null hypothesis - there is no correlation/ difference/ association

24
Q

Define H1

A

Quantitative or alternative hypothesis
there is a correlation
H1 and H0 are mutually exclusive

25
Q

What is the P value

A

The probability (chance) that the null hypothesis is true with 95% confidence. 0.05 (5%) is the statistical cut off of rejection of the H0.

26
Q

What is the true cutoff for the P value?

A

0.05/number of predictor variables

27
Q

Why is it best t under go 2-tailed tests rater than on-sided

A

A hypothesis can either be one sided or 2 sided and you can test for statistical significance in both directions. If you only test in one direction you may miss an effect in the other direction!

28
Q

What is the odds ratio?

A

A value indicating the strength of the relationship between 2 variables in data. Compared the relative odds of the occurance of the outcome of interest (cancer vs no cancer), given the exposure to the variable of interest (age)

29
Q

What does Odds Ratio mean in relationship to 1

A
  • OR = 1 variable does not effect the odds of the outcome
  • OR > 1 variable associated with higher odds of an outcome (Increase the risk of the response variable)
  • OR < 1 variable associated with lower odds of an outcome (Decrease the risk of the response variable)
30
Q

What is the Z score ?

A

Odds ratio / standard error of the odds ratio

31
Q

What are statistics tests used for?

A

To test the probability that the null hypothesis is true

32
Q

When would you use z-test?

A

When the sample size is small (n<30) and/or the population variance is known

33
Q

When would you use t-test?

A

When the sample size is small (n<30) and/or the population variance is unknown

34
Q

When would you use Chi-squared?

A

Goodness of fit - examine whether the observed results are in order with the expected values (categorical data)

35
Q

When would you use Fisher Exact?

A

Goodness of fit - gauge if there is a significant difference between proportions of the categories in two group variables

36
Q

When would you use F-test?

A

Compare variances of 2 samples or the ratio of variances between multiple groups

37
Q

When would you use ANOVA?

A

Uses F-tests to statistically test the equality of means on 3 or multiple groups of quantitaive variables

38
Q

When would you use Wilcoxon Rang

A

Test the equality of means on 3 or multiple groups - used when data is not normally distributed

39
Q

What does the result of a t- statistic mean?

A

The higher the value, the lower the chance that the two samples means are from the same population

The higher the value of t the more likely that the two samples means are to be different.

40
Q

What is a Type I error?

A

False positive

Occurs if you reject the H0 while you are supposed to accept it due to data bias

41
Q

What is a Type II error?

A

False negative

Occurs when you accept the null hypothesis when you were supposed to reject it due to a lack of power

AP0609 Component 1 (7 decks)

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