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Health Promotion 2 > Statistics > Flashcards

Statistics Flashcards

1
Q

What is Quantitative research?

A

It looks at the number, proportions and statistics. It measures things from an objective perspective to find th one truth of the population.

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2
Q

A sample of the population is usually taken in Quantitative research, what does this mean?

A

An inference is made to generalise the results to the population. This can mean that parts of the population are missed.

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3
Q

What are the key elements of statistics?

A

Data collection approach.
Data analysis.
Data interpretation.

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4
Q

What do pie charts show?

A

they show the percentage of participants and how they fall into different categories. You can compare and contrast categories.

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5
Q

What do bar charts offer?

A

They offer group comparisons to compare and contrast categories.

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6
Q

What do line graphs show?

A

they show trends over time, these can be variable or with one comparison.

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7
Q

What does a scatter plot show?

A

It shows the relationships between variables.

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8
Q

What do histograms show?

A

They are similar to bar charts but look at numbers not categories, the numbers make a difference to where they are placed.

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9
Q

What are the advantages of graphs?

A

Easily visualise a large data set.
Trends and patterns are clear.

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10
Q

What are the disadvantages of graphs?

A

Needs further explanation.
can be manipulated.
May not tell you the whole story.

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11
Q

What are the types of data?

A

Categorical
Numerical
Continuous

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12
Q

What is categorical data?

A

It can be things that are measured in categories already. There are two types, nominal and ordinal.

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13
Q

What is categorical nominal data?

A

That there is no hierarchy.

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14
Q

What is ordinal categorical data?

A

Ordered into a hierarchy.

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15
Q

What is numerical data?

A

It is countable in whole numbers or a scale that ca only be taken in certain values. It could be a tally or counting. An example could be the DMF teeth.

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16
Q

What is continuous data?

A

Can have any numbers, including decimals. There are two types, the difference is if it has a 0. Interval data, has real life meaning. Ratio data is the same but the data means something, you can’t have a negative number such as weight or height, there is no negatives.

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17
Q

What is ‘n’?

A

The number in the sample.

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18
Q

What is ‘N’?

A

The number in the population.

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19
Q

What are descriptive statistics?

A

They summarise and describe sample data.

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20
Q

What is central tendency?

A

The tendency for the value of a random variable to cluster round its mean, mode and median.

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21
Q

What is the mean?

A

This is the average or norm.

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22
Q

What is the median?

A

the middle, what separates the higher and lower values.

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23
Q

What is the mode?

A

The most common occurring result.

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24
Q

What can show the dispersion?

A

Range
Interquartile range
Standard deviation.

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25
Q

What is the range?

A

The minimum and maximum score,

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26
Q

What is the interquartile range?

A

Shows where the middle 50% of values lie, the lowest quarter and the highest quarter.

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27
Q

What is standard deviation?

A

The dispersion of data relative to the mean, the higher the standard deviation the greater the dispersion.

28
Q

What is a normal distribution?

A

Puts together central tendency and dispersion.

29
Q

What is representiveness?

A

The sample may not be representative of the population due to age, sex, experience, diet and smoking. This can lead to sampling error. Findings cannot be applied to the whole population.

30
Q

What is a sampling error?

A

A small error in measurements can shift the data which means that the central tendency is not in the same place and can make the sample biased.

31
Q

What does it mean if the data is skewed?

A

. +ve and -ve skewed is when the mean median and mode are not the same.

32
Q

What are the two tests to see if that there is normal distribution?

A

Kolmogorov-smirnov test.
Shapiro-wilk test

33
Q

What are the types of inferential statistical tests?

A

Parametric and non-parametric.

34
Q

How would you choose which inferential statistical test to use?

A

The choice is informed by:-
The type of data.
What you’re asking.
Whether the data is normally distributed.

35
Q

What is a T-test?

A

It compares the mean score between groups.

36
Q

What does a T-test mean?

A

Within participants T-test looks if scores have changes at different time points but with the same participants.

37
Q

What is the ‘P’ value?

A

It is the probability that the results is down to chance. If it is significant you can reject the null hypothesis.

38
Q

What are some T-test assumptions?

A

The data are continuous.
The sample data have been randomly sampled from a population.
There is homogeneity of variance.
The distribution is approximately normal.

39
Q

What is a WSR (Wilcoxon signed rank) Test?

A

A Non-parametric equivalent of paired T-test.

40
Q

What is a MWU (Mann Whitney U) test?

A

An independent T-test.

41
Q

What can the WSR and MWU tests be used for?

A

With non-normal distribution.
With small Samples.
With at least ordinal data.

42
Q

What test do you carry out if there are more than two groups?

A

Analysis of variance ANOVA

43
Q

What does ANOVA do?

A

It compares the mean score between more than two groups.
It tells you that there is a difference but not where it is.

44
Q

What is a P values?

A

The probability that your result is due to chance.

45
Q

What is the usual cut off for a P value?

A

P<0.05

46
Q

What is a Post HOC test?

A

It allows the exploration of difference while controlling for the possibility of false positive.

47
Q

What are some assumptions about ANOVA?

A

The dependent variable is continuous.
You have at least one categorical independent variable.
The observations are independent.
The groups should have roughly equal variances.
The data in the groups should follow a normal distribution.
the residuals satisfy the ordinary least squares assumptions.

48
Q

If the assumptions of the ANOVA aren’t met, what can be done?

A

The Kruskal-wallace test

49
Q

What is the Kruskal wallace test?

A

Non-parametric equivalent of ANOVA
Used if the distribution is not normal.
Doesn’t tell you where the difference is, jus that there is one.

50
Q

What is a Friedman’s test?

A

The non-parametric alternative for a repeated measures ANOVA.

51
Q

What is the Chi Squared test?

A

A non parametric test.

52
Q

What is the purposes of a chi squared test?

A

The test of association between categorical variables.
To test to see if observations differ from what is expected.

53
Q

What are the Chi-square assumptions?

A

Both variables are categorical.
All observations are independent.
Cells in the contingency table are mutually exclusive.
The expected value of cells should be 5 or greater in at least 80% of cells.

54
Q

What is correlation?

A

A correlation means that as one variable changes, another one will too in a specific way.

55
Q

The correlation coefficient (r) measures what?

A

Both the direction and the strength of this tendency to vary together.

56
Q

What is the Pearson’s product moment correlation.

A

Two continuous variables.
Parametric.

57
Q

What is Spearman’s rank order correlation?

A

Two continuous or ordinal variables
Non-parametric.

58
Q

What is regression?

A

Regression follows on from correlation.
It tells you how much one variable will change when another does.

59
Q

What are types of regression?

A

Simple linear
Multiple linear

60
Q

What is simple linear?

A

How one variable is affected by another.

61
Q

What is multiple linear?

A

How a variable is affected by more than one other variable.

62
Q

What are logistic in regards to regression?

A

Predicts likelihood of an event happening.

63
Q

What do you look for when reporting on regression?

A

Direction of the relationship.
R2 or correlation coefficient.
P value
Usually focus on the adjusted model.

64
Q

What is the R2 (correlation coefficient) extent dependent on?

A

Extent the dependant variable changes as the explanatory variable changes.

65
Q

What is a power calculation?

A

It is a way of ensuring that you have enough participants in your study to detect a significant difference if one exists.

66
Q

Height, temperature and time are example of what type of data?

A

Continuous data

67
Q
A

Health Promotion 2 (11 decks)

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