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Consider and discuss the required approach to fullanalysis of the data set provided.
As part of this explore also how you would test the hypothesis below and explain the reasons for your decisions. Hypothesis 1: Male children are taller than female children. Null hypothesis; There is no difference in height between male children and female children. Hypothesis 2: Taller children are heavier. Null hypothesis: There is no relationship between how tall children are and how much they weigh.
Analysis of data set
The data set is a list of 30 children's gender, age, height,weight, upper and lower limb lengths, eye colour, like of chocolate or not andIQ.
There are two main things to consider before analysing thedata. These are the types of data and the quality of the data as a sample.
Types of data could be nominal, ordinal, interval or ratio.Nominal is also know as categorical. Coolican (1990) gives more details of allof these and his definitions have been used to decide the types of data in thedata set.
It is also helpful to distinguish between continuousnumbers, which could be measured to any number of decimal places an discretenumbers such as integers which have finite jumps like 1,2 etc.
Gender
This variable can only distinguish between male or female.There is no order to this and so the data is nominal.
Age
This variable can take integer values. It could be measuredto decimal places, but is generally only recorded as integer. It is ratio databecause, for example, it would be meaningful to say that a 20 year old personis twice as old as a 10 year old.
In this data set, the ages range from 120 months to 156months. This needs to be consistent with the population being tested.
Height
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