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Proposed data collection methods

When considering the research study, there are two aspects to the survey, each requiring a different technique for data collection. The first of the aspect is to evaluate the strengths and weaknesses of the newspaper and the second is to evaluate the impact on the sales of newspapers if its features were changed.

The following procedures and techniques could be used by the colleague for accomplishing the defined goal. The data collection methods will include the qualitative as well as the quantitative paradigm. The qualitative paradigm will be used for the interviews and focus groups whereas the quantitative paradigm would include the surveys conducted by questionnaires.

If the colleague considers discussing and gathering adapt about the strengths and weaknesses of the newspaper, then a proper survey may be conducted which could allow the customer to rate the features of the product in a manner allowing the colleague to use that data in a coded form. This coded data could then be used for calculating statistical tests and variables for the survey and then provide a conclusion for the study.

In-depth interviews

An in depth interview with a knowledgeable personnel from the newspaper industry can share experiences about whether the changes in the features of the newspaper may bring changes in the overall customer satisfaction and buying preferences. This experience survey would provide a critical insight into the area of concern and will help better understand the current competitive standing of the newspaper in relation to all other newspapers published in the region.

If the colleague can not properly understand the competitive stand of the newspaper in the current market, then the expert would allow the colleague to understand what factors of the newspaper are critical in attracting customers and the target market which has been defined for the newspaper.

Focus groups

“Focus groups are used for qualitative research. These sample groups of people answer specific questions and discuss opinions, products, idea, issues to provide data for the research being done.” (Learning Essentials[1]) With the help of a trained moderator, an unstructured, free-flowing interview with a small group of participants can be conducted revealing feelings and buying preferences of customers regarding newspapers and the core requirements desired from a newspaper.

The focus groups allow a group of individuals to brainstorm on the core features or factors that affect the newspaper. All the moderator would be required to perform is throw in a question in the beginning of the session and provide an input whenever a pause in the opinions would be observed.

Observational research

An observational study at the retail outlets of newspaper stands can also be conducted where the behavior of the customers can be understood. The customers would be observed for the kinds and colors of newspapers that they may pick up for their daily reading.

This would fulfill the some of the information needs and help gather data regarding customer buying preferences and behavior. Some demographic characteristics of customers such as age and gender of the target market can also be determines by the same.

Surveys

Structured surveys can also be conducted by the colleague in order to collect some quantitative data and use this data for statistical analysis. The surveys can be considered to include factors of discussion such as rating the strengths and weaknesses of the newspaper in the perspective of the customer himself.

A survey for such a study would be developed on the basis of rating where each question would ask the rating of a certain feature of the newspaper. And then once the features have been rated, the survey may allow the respondent to fill out the rating for the newspaper in comparison to the competitors.

Such surveys allow the company to understand the competitive advantage that it has and the opportunities that it is losing out from the competitors who have certain features that attract the customers greatly. The company can then act on these surveys for further statistical inferences and decision making.

However, the colleague must be aware that for evaluating any survey results, the aspect of biasness must be made aware of because there are a number of customers who may be biased against the newspaper itself and are not willing to read it or recommend it to anyone. These results may allow the newspaper company to consider the factors that affect their biasness; however, it would be out of the scope of the current research study being conducted.

Secondary data

A number of journal articles and previously conducts research can also be used as the basis of this research. Despite the fact that the research may not be required to be elaborate, the secondary data can allow the colleague to understand how to structure the surveys and decide upon the factors to include.

As has been discussed in the previous types of data collection techniques, various authors have toughed upon the need for secondary data for a number of reasons. One of the strongest reasons is that research that was conducted in the past provides the researcher with a path to follow.

The past research acts a foundation for directing the researcher to understand the core factors which were considered within this context and it also allows the researcher to define a conceptual map in a narrow and relevant scope so that the research would be made of good use and allow the results to gloom on the newspaper revenue.

Proposed sampling plan

For the research, a simple sample frame and the considered sample have been decided upon. Using this sample the colleague can conduct the research study, collect data, and analyze the data by using some prescribed tools by the various researchers and then providing conclusions to the study.

For the observational study of the research, the colleague may use a couple of days reserved for this activity. The buying practices and behavior of customers appearing at the retail outlets would be observed on a daily basis. Since newspaper stands are almost at every street, the colleague may select five newspaper stands where he may appear and observe the buying pattern of the customers.

All the characteristics of the buyers can not be humanly noted down or observed. Since there may be a difficulty in contacting customers for the survey, the same participants may also be used for filling out the survey, despite the fact that they may or may not be readers of the same newspaper. A total of thirty individuals would be required at minimum that would have completed the survey in the proper way.

For the focus group, five respondents can be contacted by providing some kind of incentive at the end of the research or even contacting individuals who may be friends’ the distant relatives. This would be based on the convenience sampling because the focus group would only be a basis for the survey and not a complete research study conclusion on its own.

Task 2

Frequency Distribution

The frequency distribution of any data set is created by organizing the data in terms of numbers and their respective amount of occurrences in the set. Counting the occurrences and recording them is known as tallying. The frequency for a certain observation also records the amount of occurrences for each respective observation.

Following is the frequency distribution of the data:

Numbers Frequency
92 1
104 1
110 1
114 1
118 1
119 1
124 1
137 1
144 3
152 3
160 1
168 7
170 1
175 3
181 1
184 1
187 1
192 2
202 1
211 2
221 1
 Grand Total 35

Measures of Central Tendency

In order to interpret any data set, there are defined measures of central tendency that can be calculated and then sued within a certain context to describe the data set. However, in order to do so, different data sets can be defined with different measures and hence for consistency basis, there are three basic measures of central tendency that are calculated for any data series including the mean, median and mode.

For each of the below, the measures of central tendency have been defined and calculated from the given data set. Along with the calculation of the measures of central tendency, the advantages and disadvantages of the measures of central tendency are also provided in order to analyze the importance of each.

Mean

The mean of the data can be calculated by dividing the sum of the numbers by the total frequency as follows:

Numbers Frequency Mean
3265 35 93.29

The mean is the most common and useful measure of central tendency for any data set because it provides the basis for comparing two different data sets. By measuring the mean, the statistician may compare what the data sets are revealing and what conclusion can be made from them. However, a problem with the mean is that it is easily affected by extreme values.[2]

Median

The median for a specific data set would be the middle term of the data series once it is arranged in an ascending or descending order. Once the data set is arranged in a defined order, the statistician would need to locate the middle term of the data set. If the data set includes an even number of observations, the median would be found by observing the (n/2)th term.

However, for the odd number of observations in a data set, the average of the two middle terms would need to be calculated. For this data set, the median would be the (35/2)th term which is the average of the 17th and the 18th term.

Numbers Frequency Cumulative Frequency
92 1 1
104 1 2
110 1 3
114 1 4
118 1 5
119 1 6
124 1 7
137 1 8
144 3 11
152 3 14
160 1 15
168 7 22

(median falls here)

170 1 23
175 3 26
181 1 27
184 1 28
187 1 29
192 2 31
202 1 32
211 2 34
221 1 35
3265 35  

Looking at the cumulative frequency table, the 17th term of the data set equals 168 as the 18th term. Averaging the values of the two terms would provide the median for the data set. Hence, the median would be equal to 168.

The median counterparts the disadvantage of the mean which is that the median is not affected by extreme values and remains a unique and useful tool for measuring a certain data set. However, it has still not proven itself to be as popular as the mean.[3]

Mode

The mode allows the statistician to decide the most popular observation from the data set which is 168 in this case. As can be observed, the median and the mode are equal. Despite the fact that the extreme values do not affect the mode, the mode is not as popular as the remaining two measures of central tendency and a mode is not unique for a certain data set. A data set may have one or more modes at a time or may not have one at all. This creates a problem for the statistician to analyze the data correctly.[4]

Task 3

Analyzing the data set provided by the accountant it can be seen that there is a lot of vagueness in what has been presented in terms of numbers and what the accountant is trying to explain. In order to improve upon the data set, there are three ways which can be adopted:

  1. Table
  2. Chart
  3. Comparison

Each of these techniques would be described below in the mode they can be used and how they can be applied on the data set provided. As can be observed before hand, the data set is provided in a completely unorganized manner with no sense as to what each number is indicating in the series.

The accountant can create a well labeled table from the numbers allowing the reader to interpret the numbers correctly and then take action that is required. The table could provide a complete set of numbers as provided or the values could be combined into respective ranges and then the measures of central tendency can be calculated.

The accountant may also develop charts in the form of pie or bar which could help the reader in visualizing the pattern that is being depicted by the numbers. Supposing the numbers are of the revenue being generated by the company on a monthly basis, the accountant could display a trend of revenue in a simple manner.

Considering that the data can also be used in comparing historical numbers, the reader would be able to understand the comparison between the two data sets and then make the appropriate and strategic decisions.

In order to construct a spreadsheet model, the first thing that the user must have is the latest version of Microsoft Excel installed on the computer. The user can then punch in the numbers in the column format and then provide the time frame or the category to which each observation belongs on the left hand side column of the table. Once this is completed, the table can be labeled correctly.

The user can then calculate the required measurements by simply creating formulae within the cells of the spread sheet and present them in a readable and understandable manner. The core concept of developing visual aid is to allow the reader to understand the number crunching in a quick and instant manner so that the decision making may not be delayed.

The user may also create charts with the help of the Insert option where the user may select the appropriate chart format he would like to sue for displaying the data and then label the chart efficiently. The chart would also provide a clear visual aid for assisting in improved decisions.

Task 4

The basic data that has been provided from the question is as follows:

Quantity Ordered (Litres) D 25000
Batch Size (Litres) Q 800
Cost of Material (£) C 16
Ordering Cost (£) K 32
Holding Cost (£) 4
Interest Applied on Holding Cost (£) 2.4
Total Holding Cost (£) I 6.4

The economic order quantity is the quantity which optimizes the total cost of ordering and holding the material. In order to calculate the amount, following is the formula being utilized:

Q = (2KD/I)1/2

Numerator 1,600,000
Denominator 6.4
EOQ 500
  Original Cost (£) New Cost (£)
Carrying Cost 2,560 1,600
Ordering Cost 1,000 1,600
Cost of Inventory 400,000 400,000
Total Cost 403,560 403,200

The annual savings from ordering the economic order quantity would be equal to £(403,560 – 403,200) = £360.

In order to analyze the cost minimizing order size, the total cost would be calculated for each order size and then the comparison would be made. It can be observed that by ordering a larger size, the total cost of holding and ordering the inventory reduces, as is explained by the theory of economies of scale.

  Q = 500 Q = 999 Q=1000
  £ £ £
Carrying Cost 1,600 3,197 3,200
Ordering Cost 1,600 801 800
Cost of Inventory 400,000 380,000 370,000
Total Cost 403,200 383,998 374,000

 References

  1. Algebra Lesson. Retrieved on February 19, 2009 from: http://regentsprep.org/REgents/math/ALGEBRA/AD2/measure.htm
  2. Australian Bureau of Statistics. 2004. Sampling Methods. Retrieved on February 19, 2009 from: http://www.abs.gov.au/websitedbs/d3310116.NSF/4a255eef008309e44a255eef00061e57/116e0f93f17283eb4a2567ac00213517!OpenDocument
  3. Berenson, M.  & Levine, D. Business Statistics: A First Course. p. 1-100
  4. Gerson & Gerson. 2004. Technical Writing. p. 332-337
  5. Internet. 2007. Retrieved on February 19, 2009 from: http://www.statpac.com/surveys/sampling.htm
  6. Language Center. Method and Research Design. Retrieved on February 19, 2009 from: http://www.languages.ait.ac.th/el21meth.htm
  7. Learning Essentials. Retrieved on February 19, 2009 from: http://library.chisholm.vic.edu.au/coil/essentials/glossary.htm
  8. Maxwell, J. Qualitative Research Design: An Interactive Approach. p. 1-62
  9. Weiss, N. 1995. Introductory Statistics. p. 481-558
  10. Zikmund, W. 2000. Exploring Marketing Research. p. 367-459

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[1] Learning Essentials. Retrieved on February 19, 2009 from: http://library.chisholm.vic.edu.au/coil/essentials/glossary.htm

[2] Algebra Lesson. Retrieved on February 19, 2009 from: http://regentsprep.org/REgents/math/ALGEBRA/AD2/measure.htm

[3] Algebra Lesson. Retrieved on February 19, 2009 from: http://regentsprep.org/REgents/math/ALGEBRA/AD2/measure.htm

[4] Algebra Lesson. Retrieved on February 19, 2009 from: http://regentsprep.org/REgents/math/ALGEBRA/AD2/measure.htm

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