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Investigative Analytical Science > Interpreting Tables > Flashcards

Interpreting Tables Flashcards

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1
Q

What does statistics mean?

A

The science of learning from data.

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2
Q

Which are the 2 types of data sources?

A
  1. Primary data.

2. Secondary data.

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3
Q

What are the primary data?

A 
Collected specifically of investigation.
Experiments.
Observation.
Interviews.
Surveys.
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4
Q

What are the secondary data?

A 
Already compiled.
Available for analysis.
Records.
Databases.
Health data.
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5
Q

What does the frequency in a table mean?

A

The cunt in each brand category.

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6
Q

How can we analyse qualitative data?

A

Ask participants a common questions.
Make a table base on the question, the participants, and their answers.

Calculate the frequency of their answers based on the question.
Calculate the %frequency.
Cumulative frequency.
% Cumulative frequency.

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7
Q

What is the cumulative frequency when calculated in a table of dataset took from participants for a qualitative data analysis?

A

Running total of the frequency column.

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8
Q

What is the % cumulative frequency?

A

Running total of the % frequency column.

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9
Q

What do we find when they ask: ‘What % of respondents did an action?’?

A

% frequency value.

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10
Q

What do we answer when they ask :’How many respondents bought this no more than twice?’?

A

Count frequency values of nil (o) + once + twice.

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11
Q

What do we answer when they ask: ‘How many respondents bought this at least 3 times?’?

A

Count frequency values of 4 + 4 + 5 + 6 + 7 + more.

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12
Q

What is the cumulative frequency?

A

The number of individuals/items in all categories up to and including the considered category.

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13
Q

What is the cumulative percent?

A

The cumulative frequency of a categories divided by the sample size multiply by 100%.

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14
Q

How can we design a questionnaire when the question is:
‘Who buys fast food most often?’
and we need to find:
the association between age group and no. of purchases?

A

Ask respondents their age and how often they buy fast food.

Pu data on a table.

Count total of data.

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15
Q

Where do we use contingency tables?

A

For nominal.

Ordinal variables.

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16
Q

Why do we use contingency tables?

A

To record.

Analyse relationship between 2/more variables.

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17
Q

What does each cell on the dataset represent?

A

The number of items into corresponding categories.

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18
Q

Where do we have totals on a dataset table?

A

Horizontally and landscape.

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19
Q

Which is a higher outcome?:
7 out of 8 people
or
7 out of 12 people?

A

7 out of 8 people.

20
Q

What do we use when the counts are not very helpful to make them more informative?

A

Percentage.

21
Q

Where do use percentage in contingency tables?

A

For nominal and ordinary variables.

22
Q

How are the column percentages obtained?

A

(Each cell / corresponding column total ) * 100%.

23
Q

How can we calculate row percentages?

A

(Each cell / corresponding row total ) * 100%.

24
Q

How can we calculate total percentages?

A

(Each cell / sample) * 100%.

25
Q

Whatis percentage equal to?

A

Proportion.

Probability.

26
Q

If we have a SPSS Contingency table of household income v Internet use of participants.

How much is the % of internet non-users?

How much is the proportion of them?

How much is the probability of them in the sample?

A

Total amount of internet non-users / Total amount of all participants
* 100=
40%.

40%.

40% or P(internet non user) = 0.4

27
Q

How do we show the probability value of a fact in the sample?

A

P(X) = value.

28
Q

How much is the % of internet non-users with an upper household income?

A

Value of no-user upper / total non-users value * 100% = value.
Same with proportion and probability.

29
Q

How do we show the probability of a fact with another fact in the sample, known as condition probability?

A

P(X|Y) = probability of X given the condition Y.

30
Q

What will the probability of a randomly selected participant being a male who smokes be?

A

Male value / total number of participants.

31
Q

What are the marginal tools?

A

Marginal probabilities.

Total numbers of questions asked to participants.

32
Q

What is the probability of a randomly selected individual being a male?

A

Total male / total.

Not mentioned smoking/not.
Includes all cases.

33
Q

What is the probability of a randomly selected individual smoking?

A

total who smoke/total.

No gender mentioned.

34
Q

What is the probability of a randomly selected male smoking?

A

Males smoke / total males.

Only interested in male.
Only smokers.

35
Q

What is the probability that a randomly selected smoker is male?

A

Male smokers / total smokers.

Focus on smokers.
Male only.

36
Q

What are the comparing proportions?

A

Probabilities which provide evidence for/against associations.

37
Q

What is the probability that a woman has breast cancer?

A

P(D) = Total with disease/Total in study.

38
Q

What is the probability that a woman has breast cancer given she has taken HRT?

A

P(D | E) = no. taking HRT with disease / no. taking HRT.

39
Q

What is the probability that a woman has breast cancer given she has not taken HRT?

A

P(D | not E) = no. of taking HRT with disease / no. not taking HRT in study.

40
Q

What is the association between the values that a woman has breast cancer with and without HRT?

A

HRT taken –> bigger probability to have breast cancer = 0.01 > 0.007.

41
Q

What % of patients had an outcome of ‘Full Recovery’?

A

Total number of full recovery / Total number of all.

42
Q

Of patients who received a high dose, what % recovered fully?

A

High dose fully recover value / Total of high dose value.

43
Q

Of patients who made a full recovery, what % received a medium dose?

A

Medium dose dully recover / Total of fully recover.

44
Q

Of patients who died, what % received at least a medium dose?

A

Sum of medium dose value + high dose / Total of death value.

45
Q

For patients who received a low dose of drug, what % of patients had at most a minor disability?

A

Sum values of low dose of death + vegetative state + major disability + minor disability / total of low dose value.

46
Q

For patients who received at least a low dose of drug, what % of patients had at most a minor disability?

A

Sum of values 1, 2, .., until minor disability of low dose and more people /sum of low dose and more of patients.

Investigative Analytical Science (16 decks)

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