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

    University: University of Chester

    • Unit No: 6
    • Level: Undergraduate/College
    • Pages: 13 / Words 3223
    • Paper Type: PPT
    • Course Code: L/508/0442
    • Downloads: 732
    Question :
    '

    The purpose of this report is to conduct quantitative analysis through different and effective methods that can assist in gathering more reliable information for business purpose. Quantitative methods of calculation represent mathematical data for which individual needs to have specific knowledge in such areas.

    • Determine an application of different quantitative methods and gather authenticate information from its effective uses.
    '
    Answer :

    INTRODUCTION

    Quantitative assessment implies for the evaluation of data set through the means of statistical tools as well techniques. In the recent times, business unit laid high level of emphasis on undertaking quantitative tools and techniques for the purpose of decision making. Statistical tools and techniques are highly significant which in turn helps in drawing suitable conclusion from data set. The present report is based on different case situations which will provide deeper insight about the manner in which tools such as descriptive statistics aid in decision making. Further, report also presents how regression analysis helps in determining the impact of one variable on another.  It also depicts the use of probability evaluation or assessment in decision making.

    QUESTION 1

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

    Measures of Variability and Association

    Class interval

    Number of passengers at each train station in Melbourne

    Cumulative  frequency

    Relative frequency

    Cumulative relative frequency

    mid point

    169-468

    19

    19

    0.32

    0.32

    403

    469-768

    12

    31

    0.20

    0.52

    853

    769-1068

    9

    40

    0.15

    0.67

    1303

    1069-1368

    8

    48

    0.13

    0.80

    1753

    1369-1668

    5

    53

    0.08

    0.88

    2203

    1669-1968

    2

    55

    0.03

    0.92

    2653

    1969-2268

    1

    56

    0.02

    0.93

    3103

    2569-2868

    2

    58

    0.03

    0.97

    4003

    2869-3168

    1

    59

    0.02

    0.98

    4453

    7669-7968

    1

    60

    0.02

    1.00

    11653

    Grand Total

    60

     

     

    Histogram

    Bin

    Frequency

    169

    1

    1249

    45

    2329

    10

    3409

    3

    4489

    0

    5569

    0

    6649

    0

    More

    1

     

    3. Descriptive statistics

    Computation of mean, mode and median

    Number of passengers at each train station in Melbourne

    Particulars

    Outcome

    Mean

    1033.43

    Standard Error

    141.11

    Median

    715

    Mode

    401

    Standard Deviation

    1093.04

    Sample Variance

    1194731

    Kurtosis

    23.78

    Skewness

    4.21

    Range

    7560

    Minimum

    169

    Maximum

    7729

    Sum

    62006

    Count

    60

     

    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

    S. No.

    Weekly attendance

    1

    472

    2

    413

    3

    503

    4

    612

    5

    399

    6

    538

    7

    455

    Standard deviation

    74.1

     

                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 1st quartile from the 3rd one interquartile range can be assessed.

    Calculation of inter-quartile range

    Particulars

    Number of chocolate bars sold

    6916

    5884

    7223

    8158

    6014

    7209

    6214

    1st quartile

    6114

    3rd quartile

    7216

    Inter-quartile range (3rd quartile – 1st quartile)

    1102

     

    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

    Weekly attendance

    Number of chocolate bars sold

    472

    6916

    413

    5884

    503

    7223

    612

    8158

    399

    6014

    538

    7209

    455

    6214

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