Summarising Data Flashcards

1
Q

What is an average

A

A single value used to describe a data set

It is a measure of central tendency

The mode median and mean are averages

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2
Q

What is the mode

A

The value which is most often

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3
Q

What is the median

A

The middle value

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4
Q

When the number of the data sets values are odd how do you find the median

A

It is the 1/2(n+1) observation

Where n is the number of values

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5
Q

How do you calculate the mean

A

Sum of x(÷n)

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6
Q

What is the mode in classed frequency data

A

The category / class with the highest frequency

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7
Q

How do you find the median category in frequency table data

A

It is the class that contains the 1/2(n+1)th value

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8
Q

What is the modal class

A

The class with the highest frequency

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9
Q

How do you find the median for continuous data

A

It is the 1/2nth value

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10
Q

What is linear interpolation

A

A method used to estimate the median value in grouped data

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11
Q

How do you find the median / a quartile using linear interpolation

A

Find where the median is in the grouped data. This is done by finding the position, and then using cumulative frequency to see which group it is in.

Find out how far into the group your median is in

Then use the formula

(Median value - cumulative frequency before ÷ change in cumulative frequency) × class width

Basically what you are doing finding how far into the group your value is, finding this in proportion to the values in your group and multiplying by the class width

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12
Q

How do you calculate an estimated mean from grouped data

A

Sum of (f×midpoint) ÷ sum of f

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13
Q

What happens to the averages when you increase / decreases by a set percentage

A

The averages increase or decrease for a set percentage

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14
Q

Why do we transform data

A

To make it easier to calculate the mean

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15
Q

How do you transform data with decimals

A

Subtract each decimal from the same integer

Then multiply them until they are whole numbers

Now calculate your average

Then reverse the calculations you did to find a mean (divide by your multiple of 10 and add your number)

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16
Q

What is a geometric mean

A

An average that multiplies all the values and roots the number

It is more accurate and effective than using an arethmatic mean

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17
Q

How do we calculate geometric mean

A

n√v¹×v²×v³ etc…

N is the number of values
The values are rooted by n

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18
Q

Why are weighted means used

A

For data with different values or weightings in each group

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19
Q

How are weighted means calculated

A

Sum of (value × weight) ÷ sum of weights

(Total wx) ÷ total w

20
Q

What is a range

A

Largest value - smallest value

21
Q

What is an interquartile range

A

Upper quartile - lower quartile

22
Q

What are the upper and lower quartiles

A

Upper = 3/4 th value

Lower = 1/4 th value

23
Q

How do you calculate quartiles in discrete data

A

The same ways as means but using the quartiles as a fraction rather than 1/2

E.g 1/4(n+1)

24
Q

How do you calculate the range in a frequency table

A

Take the largest possible value and smallest possible value from the table

Subtract these values

25
How do you calculate quartiles in continuous data
The same way you would calculate the median in continuous data E.g 1/4(n)
26
What are percentiles
When a data set is divided into 100 equal parts
27
What are deciles
When data is divided into 10 equal pwrts
28
What is an interdecile / interpercentile range
The difference between two percentiles or deciles
29
What is standard deviation
A measure of how far the values deviate from the mean value
30
How do you calculate standard deviation
√(sum of x^2 ÷n)-(mean)^2 Where n is the number of values
31
How do you calculate standard deviation for grouped data
√(sum of f×x^2 / sum of f) ÷ (sum of fx / sum of f)^2
32
What does a blox plot show
Maximum and minimum values Median Upper and lower quartiles
33
How do you find an outlier using quartiles
Small outlier < (lq - 1.5×iqr) Large outlier > (uq + 1.5×iqr)
34
How do you find an outlier using standard deviation
Mean + / - (3×standard deviation)
35
What are the 3 types of skew
Symmetrical distribution - median in the centre Positive - median closer to lower quartile Negative - median is closer to upper quartile
36
What does mean>median>mode indicate
Positive skew
37
Mode>median>mean indicate
Negative skew
38
How do you calculate skew
3(mean-median) / standard deviation
39
Advantages and disadvantages of using the mode to show average
A: Easy to find Can be used with any data type Unaffected by open-ended or extreme values Mode is always a data accurate value D: Maybe no mode or multiple modes Cannot be used to calculate a measure of spread
40
Advantages and disadvantages of using the median to show average
A: Easy to calculate Unaffected by extreme values Best to use when data is skewed Can be used to calculate quartiles D: May not be a data value
41
Advantages and disadvantages of using the mean to show average
A: Uses all the data Can be used to calculate standard deviation (statistical calculations) D: Always effected by extreme values Can be distorted by open ended classes
42
What do you need to do when comparing data sets
You need to compare an average and a measure of spread Also you can compare the measure of distribution
43
What is the distribution in a box plot like
50% of data is less than the median 50% of the data is more than the median 25% of the data is less than the lq 25% of the data is greater than the uq 50% of the data is between the quartiles
44
Linear interpolation example Estimate the median amount of time spent watching tv Median = 12th term Median group = 10
The median is found 2 into the group LCB + amount into group / group total × class width 10+ 2/20 × 5 = 11
45
What does it mean to transform data
To alter data in order to make calculations easier. Once you have finished your calculation you must re transform the data back