Essays on Analysis of Crop Production Index in the United Kingdom Case Study

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The paper "Analysis of Crop Production Index in the United Kingdom" is a perfect example of a business case study.   Crop production analysis is an important aspect in any country in order for the country to plan on either importing in the period of low crop production or exporting excess crop product. This will assist in improving a country’ s food security, reduce wastage and increase a country’ s national income from export of excess produce. Therefore, to come into a conclusion we had to take several measures of central tendency, hypothesis testing and the relationship between variables in order to predict the future trend and draw appropriate strategies to ensure that the United Kingdom has proper measures to deal with food insecurity. 1.0 DATA OVERVIEW The data analyzed is based on crop production index in the United Kingdom starting from 1961 to 1976 showing a range of data obtained from a period of 15 years.

The data is numerical with two variables independent variable (Years) and dependent variable (Crop production index). The data is an extract from the World Bank database containing data from 1961 to 2011.

The data is as shown in the table below (appendix 1). 2.0 DATA DESCRIPTIVE STATISTICS AND VISUALIZATION 2.0.1 Mean Mean (µ ) = x= Middle age in each class µ = mean f = Frequency of in each class n = Sample size µ = µ = Therefore, mean (µ ) = 74.44 This means that the central or average of the crop production index in the United Kingdom from 1961-1976 is at 74.44. Mean favorable as a measure of central tendency when the distribution is normal. Skewness is determined by the variation between median and mode. When the median is equal to mean the distribution is normal while when there is variation distribution is either positively or negatively skewed (Chikkodi & Satyaprasad, 2010) 2.0.2 Median Crop production index Frequency Cumulative frequency 55.5-58.5 1 1 58.5-62.5 1 2 62.5-66.5 2 4 66.5-70.5 3 7 70.5-74.5 3 10 74.5-78.5 4 14 78.5-82.5 1 15 ½ (n term) where n is the sample size ½(15) =7.5th term Median class= 70.5-74.5 Median= Lm+ [] i Where n= sample size F= cumulative frequency of the preceding class f=frequency of the median class i=Class width Lm= Lower class boundary Median=70.5+ [] 4 =70.5 + 0.5 = 71.17 From calculation 71.17 is the production index that separates the lower and upper half of the production index from 1961 – 1976.

It works the same as mean but it is most favorable in skewed distribution since it is less affected by the variety of data (Mendenhall and Sincich, 1986). From the data above we found out that median is the most appropriate in making inference of on measure since the data is slightly skewed to the left. 2.0.3 Mode This is the value that is appearing many times compared to other value and therefore there is a higher possibility of occurring future or sampling out.

From crop production index mode is given as follows; Mode= Lmo + [] i Lmo= Lower class boundary of mode class Δ 1 = difference between the frequency of the modal class and the class after modal class frequency Δ 2= the difference between the mode class frequency with the frequency of proceeding class i= Mode class width Mode class= 74.5-78.5 Δ 1= (4 - 1) = 3 Δ 2= (4 - 3) =1 i =4 = 74.5+ [] 4 =74.5 + 6 =80.5 Therefore, the model of crop production index is 80.5 showing a high possibility of the country recoding 80.5 crop production index in future.

It can be used in forecasting though it is not the best option since it doesn’ t have a high degree of certainty.

REFERENCE

Chikkodi, C. M. and Satyaprasad, B. G. 2010. Business statistics. Mumbai: Himalaya Pub. House.

World Bank. 2014. United Kingdom | Data. [online] Available at: http://data.worldbank.org/country/united-kingdom [Accessed: 18 Mar 2014].

Brown, S. 2014. Measures of Shape: Skewness and Kurtosis / MATH200 / Brown, TC3. [online] Available at: http://www.tc3.edu/instruct/sbrown/stat/shape.htm [Accessed: 18 Mar 2014].

Gupta, C. B. 2007. Quantitative methods. New Delhi: Asian Books.

Mendenhall, W. and Sincich, T. 1986. A second course in business statistics: Regression analysis. Dellen Publishing Company San Francisco, CA.

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