Maths- statistics 1

Created by: shona
Created on: 26-12-12 16:13

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Maths- statistics 1
- averages and range
  - mode
    - most common
  - median
    - the middle number once arranged in order
  - mean
    - the sum of all values divided by the total number of values in the set
      - mean= sum of all values/ total number of values
  - range
    - the difference between the highest and lowest values in a set
      - range= highest-lowest
- frequency tables
  - when data is represented it can be put in a frequency table
  - find the mode by looking for the data value that has the highest frequency
  - find the median by adding up all the frequencies in order until half way point of all data is passed
  - find the mean by multiplying the value of each data by its frequency adding the totals and dividing by the total of all the frequencies
- grouped data and frequency diagrams
  - when there is a wide range of data with lots of values there are often too many entries for the frequency table
    - so you will use a grouped frequency table
  - in a grouped frequency table data is recorded in groups like 10< x<20
  - grouped data can be shown in a frequency polygon
  - the modal class is the group with the greatest frequency
  - median cannot be found from grouped frequency tables
  - calculate an estimated mean by adding the midpoints multiplied by the frequencies and dividing by the total frequency
- histograms
  - similar to a bar chart but continuous data only ( time or weight)
  - the horizontal axis
    - has the continuous scale and there are no gapes between the bars
  - the area of each bar represents the frequency of the bar
  - the height of the bar is called the frequency density
    - frequency density= frequency class interval/ width of class interval
  - the median is the value where the area of both is equal
  - the lower quartile is the value that splits the area in the ratio 1:3
  - the upper quartile is the value that splits the area in the ratio 3:1
- the data handling cycle
  - outlining the problem and planning
    - usually involves a hypothesis
  - stating how the data will be collected
  - saying how the data will be processed and represented
    - usually involve working out means and measures of spread and showing the data in a suitable diagram
  - interpreting the results and making a conclusion
    - this should relate to the original hypothesis or problem
- data and data collection
  - qualitive
    - this is data such as colour of cars
  - discrete quantative
    - this is numerical data that can only take certain values such as the number of people on a bus
  - continuous quantative
    - this is numerical data that can take any value in a range of values such as the weight of apples
  - primary data
    - this is data collected using surveys or experiments
  - secondary data
    - this is data collected from existing tables or lists
  - look at historical data
    - this would be used to predict whether it will rain on the 4th july in Edinburgh for example you would look back at records for all previous years
  - experiment
    - this would be used to test the probability of an event that cannot be predicted such as how many blue balls in a bag
  - equally likely outcomes
    - this is used when the probability of an event can be predicted for example taking a king from a pack of cards
  - surveys
    - this is used when there is no historical data and no way to predict probabilities a survey could be used to find what subject is the favourite amongst year 7 pupils
when talking about the average its the same as the mean
the lower quartile is the value that splits the area in the ratio 1:3
there are four parts to the data handling cycle
usually involve working out means and measures of spread and showing the data in a suitable diagram
there are different types of data
depending on what is being investigated there are four different ways to collect data

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Maths- statistics 1

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