# Maths- statistics 1

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