L/508/0442 - Quantitative Methods Of Calculation Represent Mathematical Data

QUESTION 1

a. Stating the Frequency, Relative Frequency, Cumulative Relative Frequency and Class Midpoint

Measures of Variability and Association

 

Histogram

 

3. Descriptive statistics

Computation of mean, mode and median

 

The above depicted table of descriptive statistics show that average number of passengers at each train station in Melbourne accounts for 1033 respectively. Further, outcome of descriptive statistics present that 50% value of data set and median value implies for 715 significantly. Along with this, it has assessed from the evaluation that mode is 401. On the basis of this, it can be presented that 401 passengers repeatedly arrived at each train station in Melbourne for the weekday peak time such as 7 am to 9.29 am.      

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QUESTION 2

a. Assessing whether above given data comes under population or sample

            From research, it has found that data set given in relation to the weekly attendance in Holmes and number of chocolate bars sold. Referring given case, it can be presented that manager of supermarket wants to assess whether there is any relationship takes place between the students who attending class and sales of chocolate bars. Hence, in this, whole students of Holmes have been considered. Thus, by taking into such aspects it can be presented that given data set implies for population rather than sample. Moreover, sample is the small part of population, whereas population accounts for the whole target. Hence, it can be mentioned that given data set includes population. Through assessment, it has identified that significant difference takes place between sample and population (Cressie, 2015). Moreover, population implies for the collection of all elements who possess common characteristics that comprise universe.  

b. Calculating standard deviation of the weekly attendance

Computation of standard deviation

 

            Findings of statistical assessment presents that in the near future mean value will deviate from the figure of 74.1 respectively.

3. Inter-quartile range assessment

Interquartile range may be swerved as a viability measure which divides or distinguishes whole data set into quartiles. By subtracting 1^st quartile from the 3^rd one interquartile range can be assessed.

Calculation of inter-quartile range

 

4. Assessing correlation co-efficient

Correlation is the most effectual statistical tool which helps in assessing the extent to which two variables are associated with each other. In other words, it helps in assessing the level to which one variable will move when changes take place in another. 

Correlation co-efficient