Reflection Essay on Business Decision Making

The methodology for this report will focus upon both primary and secondary research methods which will be used to obtain the opinions of the asked passer. Needled et-al  states that primary research mainly consists of data collected by an organization, or individual, for their own purposes and are generally collated first hand from 'the horses mouth'. Needled  offers the opinion that the main methods of collating primary research are through conducting face to face Interviews, telephone interview, questionnaires and through direct observations.

Primary data can be either qualitative or quantitative. Qualitative research data tend to be more explanatory whereas quantitative is generally more descriptive. The main part of the research for this project will consist of one primary method, survey. The survey questioned passers within Princess to determine what they think about the Princess. This method has been chosen as it is easy method to collate considerable data and it is a relatively cheap method of collating the data.

To ensure response rates were high, the passers were asked face to face. I have chosen to opt against a paper based System as Needled et-al (2003) offers the argument that response rates to costal systems are often as low as 30% and I feel this method may introduce bias to the overall conclusion. There the alternative option of personally distributing and collecting the surveys for which Sweeten  claims can increase the response rate to almost 70%.

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However given the short timescales for the project I only intend to sample the views of 20 people. Questionnaires are quite popular when collecting data, but are difficult to design and often need many drafts before having a final questionnaire. These drafts are called pilot questionnaires. Again because of the given short time call I was only able design one pilot. It emerged that the questionnaire was too long. The final questionnaire was then amended by the KISS theory'- keep it short and simple.

Random sampling was used as non random sampling is impracticable and often very costly in terms of time. After collecting the primary data, the data was then exported into Microsoft Excel to provide a more professional presentation for this document in providing professional graphs and findings. Secondary research All methods of data collection supply quantitative data (numbers, statistics) or qualitative data (usually words or text).

Secondary data is data that has already been collected by someone else for a different purpose as the investigator. Main methods that is used to for the collection Of secondary data: Data supplied by a marketing organization Annual company reports Government statistics / surveys Academic surveys Company data (payroll details, minutes of meetings, accounts of sales of goods or services) Whilst theory is a crucial factor in academic learning and organizational success leading academics offer different views on it effectiveness.

Saunders et-al explains that secondary research, especially academic journals, re the most important source for any research because they are evaluated by academic peers prior to publication therefore generally of good quality. Gharry  offers the opinion that secondary research is has there are major advantages of secondary research mainly through savings in time, money and resources as academic literature from various sources is widely available and easily obtainable.

However Needled et-al warns that the information may not always be of good quality, may not represent the whole picture and the research could be out of date. These opinions were considered whilst conducting the literature review. After having contacted the Princess press department the result was that due to the fact that the Princess is a new development, secondary data was not available. Rest Its The layout of the questionnaire was divided in three parts - introductory questions, main questions and final questions.

What do you think of the Princess development? Number of questioned people: 20. The introductory questions are of assistance to find out general information about the questioned person.

1. Gender
2. Age group
3. Employment status
4. . Marital status
5. Purpose of the visit
6. Preferred time to visit
7. Does it meet expectations?
8. What were the expectations?
9. Affect on Setter's other high street retailers and restaurants 1
10. Overall affect of the Princess Shopping Centre to Exeter Final questions. The final questions help to calm down and relax from the main part. It can also seen as fun part.
11. Favorite new shop 1
12. Favorite new restaurant/cafe

The Upper Crust Memo To: Quality Control Manager From: Tugboat Vic Sicken c: Date: January 31, 2015 Re: Result of samples 65 loaves of bread with a weight range of 780-830 g Average weight (mean) of loaves 804. 74 g The middle loaf (median) weighs 804. 9 g The most common (mode) loaf weight is 804. 9 g The Standard deviation of each loaf is 9. G The weight of the lower quartile is (IQ) is 798. 48 g Q = Median = 804. 9 g The weight of the upper quartile is (Q) is 811. 1 g The intrauterine range is 12. 62 g Box + Whisker plot Due to wastage we lost 805 loaves Task 5 Correlation The correlation is one of the most common and most useful statistics. A correlation is a single number that describes the degree of relationship between two variables. If points in scatter diagram cluster close to the line then there is a strong correlation in place and if points are more widely scattered the correlation is weak.

Positive correlation If an increase in one variable tends to be associated with an increase in the other then this is known as a positive correlation. An example would be height and weight. Taller people tend to be heavier. Negative correlation If an increase in one variable tends to be associated with a decrease in the other then this is known as a negative correlation. An example would be height above sea level and temperature. As you climb the mountain (increase n height) it gets colder (decrease in temperature).

A zero correlation occurs when there is no relationship between variables. The picture below shows a guide to the strength of correlation Strengths of correlations. Correlation enables the researcher to examine naturally occurring variables that perhaps unethical or impractical to test experimentally. For instance, it would be unethical to carry out an experiment on whether smoking causes lung cancer.  Correlation enables the researcher to clearly and easily see if there is a relationship between variables. This Can then be displayed in a replica form.

Limitations of correlations 1 . Correlation is not and cannot be taken to imply causation. Even if there is a very strong relationship between two variables we cannot assume that one causes the other. For example suppose we found a positive correlation between watching violence on T. V. And violent behavior in teenage years. It could be that the cause of both these is a third (irrelevant) variable - say for example, growing up in a violent home - and that both the watching of T. V. And the violent behavior are the outcome of this. . Correlation does not allow us to go beyond the data that is given. For example suppose it was found that there was a relationship between time spent on homework (112 hour to 3 hours) and number of G. C. S. E. Passes (1 to 6). It would not be correct to conclude from this that spending 6 hours on homework would be likely to generate 12 G. C. S. E. Passes 5 A + B. Rest It: The older the car gets (increase) the less is it worth (decrease). The scatter diagram above shows that the correlation is stronger after the first two years.

There is no straight line relationship. The points on the graph with couple of exceptions form a curve which suggests it is not a linear relationship. The explanation of partial in the correlation result means that it is not 100% correlated because of other factors that influenced it. Coefficient of determination: 65. 61 % of the behavior of y is determined by x + 34. 39 % by other factors. The aim of regression analysis is to find out the values of parameters for a function that cause the function to best fit a set of data observations that it's provided.

In linear regression, the function is a linear (straight-line) equation. The equation and the table above show that the value of the car decreases by a constant amount each year after its purchase. The following linear function loud predict its value Value = price + departed*age Value, the dependent variable, is the value of the car, age is the age of the car. The regression analysis will determine the best values of the two parameters, price, the estimated value when age is O (I. E. , when the car was new), departed, the depreciation that takes place each year.

The value of departed will be negative because the car loses value as age increases. However as we can see in the table after 12 years the equation gives a negative value. This would be not possible in reality. A car cannot be worth E-340. 06. The problem with the equitation is that it is not realistic. The equation is only correct in terms Of figures. E. The equation does not include the factors that can influence the price of a used car. It only considers the age of the car. However there can be several other factors that can influence the price of a used car.

Mileage Color- In other words, some colors, like "ROI Yellow Pearl", appeal only to a small segment of the population and brings down the car's worth in many eyes Fuel type Engine size Transmission Number of doors Private or trade seller - Trade seller are always more expensive as trader adds profit on the actual value of the car. Previous owner - For example if a elderly person was the previous owner it is very likely that the car was only used for short distances (shopping, doctor consultations) On the other hand if the car was used at a driving school then it is very likely that the car was not treated well from the learners. F. Business decision makers need to find out very often the casual relationship between two variables. For instance, the relationship between interest rates and consumer expenditure. Furthermore a financial analyst may use regression and correlation to help understand the relationship of a financial ratio to a set of other variables in business. Correlations can be helpful in business. Once a correlation is identified, organizations can determine if the correlation indicates causation. With this information, the company can develop methods to influence the correlation to the organization's benefit.

The longest the start of an activity can be delayed from its earliest start time (EST) without delaying the project. Free float The longest an activity can be delayed from its EST without delaying the EST of any immediately following activities. By looking at the table, those tasks without a total float' (I . E. Zero) are considered 'critical' and coincidentally are mound on the critical path. It is therefore important that these tasks are not delayed in order to complete the project on time as planned.

Recognizing and integrating float is very important. For example, those tasks that do carry float may have resources (labor, capital, equipment, etc) that could be used elsewhere to complete other tasks quicker. Also, for those tasks that do carry float, any delays can be accepted. As the resource diagram below shows, 6 assistants are required for the job. Furthermore the whole procedure will take 25 days. After rescheduling the activities only 4 assistants are required. Apart from this the whole procedure will take 21 days.

Critical Path Analysis (CPA) is a planning and project management tool. It can help make sure a project is completed as quickly as possible, and resources used as efficiently as possible. The business is able to give the customer exact information such as finish date, required assistants. Furthermore, most projects come across with delays or something unexpected, so managers need to use tool such as CPA to monitor the project and take quick action to resolve any problems. This enables the business to avoid any delays and the consequential customer complaints.

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