Questions:
 Analysis of sales and country data, forecasting of sales figures until 2020
 Market place Sweden – Estimate of potential sales figures in 2016 and forecast to 2020
 Analyse and present data graphically using spreadsheet software (Excel).
 Critically evaluate summary statistics against suitable benchmarks.
 Apply judgement to select appropriate methods of data analysis drawing on knowledge of regression analysis, probability, probability distributions and sampling distributions.
 Select and apply a range of data analysis tools to inform problem solving and decision making.
 Conduct quantitative research both individually and as part of a team and articulate and present findings to a wide range of stakeholders, from accounting and nonaccounting backgrounds.
Answers:
Introduction
The Board of Directors of the Schmeckt Gut has sales from three countries which includes Industria, Nokaragua and the Federated Island. The board of directors has ensured the sale of the past twenty five years has been recorded. The data provided was analyzed using descriptive be used in prediction of sales for the five years to come. The newly expansion of the Schmeckt Gut in Sweden is point of interest for the board of directors to also now the potential sale in the five years to come Statistics and also inferential statistics. The Board of Directors requires a forecast model that will
Analysis of sales and country data, forecasting of sales figures until 2020
Overview analysis of the data
The data provides the sales figure in US$ exempting the newly opened which is Sweden, the GDP data in US$, average price index (in %), the population for persons aged 15 – 65 years, survey score for customer satisfaction, number of average advertisement and number of scores.
Industria 1

Coefficients 
Standard Error 
t Stat 
Pvalue 
Intercept 
0 
#N/A 
#N/A 
#N/A 
GDP US$ 
0.024568308 
0.036976687 
0.664426949 
0.514401 
Price index 
0.266843767 
0.018125986 
14.72161385 
7.65E12 
Population 1565 
0.836051117 
0.039904454 
20.95132313 
1.37E14 
Survey score 
0.178619201 
0.059815627 
2.986162831 
0.007591 
Advertisement 
0.512402307 
0.150781794 
3.398303554 
0.003016 
Stores 
0.450532969 
0.253939828 
1.774172143 
0.092061 
Statistical interpretation
The table above provides an analysis of the pvalues in the price index, population of persons between 1565 years, survey score and advertisement are less than level of significance 0.05 thus we conclude that they are significant to the Industria country. The pvalue of number of stores in Industria is greater than level of significance 0.05 thus they are not sufficient for persons in Industria country.
Nokaragua

Coefficients 
Standard Error 
t Stat 
Pvalue 
Intercept 
0 
#N/A 
#N/A 
#N/A 
GDP US$ 
0.236433914 
0.039740882 
5.949388 
1E05 
Price index 
0.032264777 
0.006566533 
4.91352 
9.65E05 
Population 1565 
0.483241266 
0.059844242 
8.074984 
1.46E07 
Survey score 
0.144253973 
0.027318231 
5.280502 
4.27E05 
Advertisement 
0.360209578 
0.086920562 
4.144124 
0.000551 
Stores 
0.315096665 
0.055014483 
5.727522 
1.61E05 
Statistical interpretation
In Nokararagua country the GDP, price index, population of persons aged between 1565 years, survey score, advertisement and stores have pvalues less than the level of significance 0.05 hence we conclude that they are significant to the running of the Schmeckt Gut in these country. The numbers of store here are enough to serve the population present here unlike the case of Industria country.
Federated Island1

Coefficients 
Standard Error 
t Stat 
Pvalue 
Intercept 
0 
#N/A 
#N/A 
#N/A 
GDP US$ 
0.205247077 
0.154118182 
1.331751219 
0.198698856 
Price index 
0.15767235 
0.052124715 
3.024905768 
0.006966417 
Population 1565 
0.833930629 
0.30016399 
2.77825008 
0.011977372 
Survey score 
0.123452577 
0.075146765 
1.642819572 
0.116867278 
Advertisement 
0.627153351 
0.279416177 
2.244513394 
0.036902494 
Stores 
0.006708251 
0.232259441 
0.028882577 
0.977259465 
Statistical interpretation
In the Federated Island the case is different as compared to Industria and Nokaragaua. The GDP, survey score, number of store have pvalues greater than 0.05 thus don’t lie within the acceptance region and thus need to be controlled. The GDP is doesn’t have acceptance in the country, the customers score rating didn’t meet the expectations and the number of store were not sufficient to serve customers. The price indexes, population of persons between 1565 years and advertisement have the pvalues that are less than the level of significance and hence they fall within the level of acceptance.
Correlation Analysis
Industria 1
The sale development is highly influenced by advertisement, number of stores available and the survey results from the customers.

Advertisement 
Stores 
Advertisement 
1 

Stores 
0.969905466 
1 

Survey Score 
Stores 
Survey Score 
1 

Stores 
0.230785592 
1 

Survey Score 
Advertisement 
Survey Score 
1 

Advertisement 
0.20232024 
1 
The advertisement of the different store in the country has a highly positive correlation 0.9699 which means the more the advertisements of the stores are done higher number of customers is experienced. There exist a weak negative correlation between the survey results and stores. The responses obtained from the survey about the stores indicates that only customers with complain tend to answer the survey or they are not satisfied by the services. The survey score and advertisement have a weak negative correlation 0.2023 which mean the customers who visit the store don’t find the advertisement being influential enough.
Nokaragua

Advertisement 
Stores 
Advertisement 
1 

Stores 
0.992123908 
1 

Survey Score 
Stores 
Survey Score 
1 

Stores 
0.011010721 
1 

Survey Score 
Advertisement 
Survey Score 
1 

Advertisement 
0.002906977 
1 
The advertisement of stores in Nokaragua country has a strong positive correlation 0.9921 thus the more stores are advertised the more customers tend to visit them. The survey score and store have a weak positive correlation 0.011 which mean customer have a positive attitude towards the stores. The survey score and advertisement have weak positive correlation which means that customers are visiting the store after seen the advertisement.
Federated Island1
Correlation Coefficient 
Advertisement vs. Stores 
0.967583 
Advertisement vs. Survey score 
0.610625 
Survey score vs. Stores 
0.640619 
The table above shows a strong positive correlation between the advertisement and stores of 0.9675 the more stores are advertised the more customers tend to visit the store and hence sales are experienced. The survey score and advertisement have a strong positive correlation of 0.610625, customer who visit the store are optimistic about the advertisement and conclude that it has increased visitation. The number of stores in the Federated island and the survey score have a positive correlation 0.6406, the number of store are strategic located and enough to serve customers effectively.
Multi Regression Time Series Analysis
Industria 1

Coefficients 
Standard Error 
t Stat 
Pvalue 
Lower 95% 
Upper 95% 
Lower 95.0% 
Upper 95.0% 




Intercept 
0 
#N/A 
#N/A 
#N/A 
#N/A 
#N/A 
#N/A 
#N/A 




GDP US$ 
0.024568308 
0.036976687 
0.664426949 
0.514401 
0.05282 
0.101961404 
0.052824789 
0.101961404 




Price index 
0.266843767 
0.018125986 
14.72161385 
7.65E12 
0.30478 
0.228905642 
0.304781892 
0.228905642 




Population 1565 
0.836051117 
0.039904454 
20.95132313 
1.37E14 
0.75253 
0.9195721 
0.752530135 
0.9195721 




Survey score 
0.178619201 
0.059815627 
2.986162831 
0.007591 
0.053424 
0.303814747 
0.053423656 
0.303814747 




Advertisement 
0.512402307 
0.150781794 
3.398303554 
0.003016 
0.196812 
0.827992229 
0.196812386 
0.827992229 




Stores 
0.450532969 
0.253939828 
1.774172143 
0.092061 
0.08097 
0.982035137 
0.080969198 
0.982035137 




Statistical interpretation
H0: The GDP influences the sales development
H1: The GDP has no influence on the sale development
The level of significance in these case is alpha= 0.05
The pvalue 0.5541 which is greater than the level of significance 0.05 hence we reject the null hypothesis and conclude that the GDP doesn’t influence the sale development of the stores. The GDP despite being high or low the sale development remains to be the same. Customers buy the good and services under all conditions.
H0: Prices of commodities from stores influence sales development
H1: Prices of commodities doesn’t influence sale development
The alpha=0.05
The pvalue is 7.65*10^6 which is less than the level of significance 0.05 hence we fail to reject the null hypothesis and conclude that the price of commodities influence the sale development. The price of a commodity from the store which are friendly price then the sale development will increase accordingly.
H0: Population development influences sale development
H1: Population development doesn’t influence the sale development
The pvalue is 1.37 * 10^12 is less than the level of significance 0.05 thus we reject null hypothesis and conclude that population development doesn’t influence the sale development. The population may increase and the sale to remain same. The sale development isn’t influenced by population increase
Forecast model
Sales US$=0.04256*GDP0.2668*price index+0.83605*population+0.178619*survey score+0.5124*advertisement+0.4505*stores
The regression model above is used to predict the sales development to the year 2020. The GDP in this model contributes 4.25% of the sales development, population of persons aged 1565 years contributes 8.36% of the sales, survey score contributes 17.86% of the sale, level of advertisement contributes to sales development by 51.24% and store strategic location, number of stores contributes 45.05% of sales development. The price indices show negative percentage 26.68% of the model. The prices in the stores should be catered for to ensure high sales.
Nokaragua 1

Coefficients 
Standard Error 
t Stat 
Pvalue 
Lower 95% 
Upper 95% 
Lower 95.0% 
Upper 95.0% 
Intercept 
0 
#N/A 
#N/A 
#N/A 
#N/A 
#N/A 
#N/A 
#N/A 
GDP US$ 
0.236433914 
0.039740882 
5.949388 
1E05 
0.153255 
0.319613 
0.153255 
0.319613 
Price index 
0.032264777 
0.006566533 
4.91352 
9.65E05 
0.04601 
0.01852 
0.04601 
0.01852 
Population 1565 
0.483241266 
0.059844242 
8.074984 
1.46E07 
0.357986 
0.608497 
0.357986 
0.608497 
Survey score 
0.144253973 
0.027318231 
5.280502 
4.27E05 
0.087076 
0.201432 
0.087076 
0.201432 
Advertisement 
0.360209578 
0.086920562 
4.144124 
0.000551 
0.178283 
0.542136 
0.178283 
0.542136 
Stores 
0.315096665 
0.055014483 
5.727522 
1.61E05 
0.19995 
0.430243 
0.19995 
0.430243 
Statistical interpretation
H0: The GDP influences the sales development
H1: The GDP has no influence on the sale development
The pvalue of the GDP population is 0.00001 which is less than the level of significance which is 0.05 hence we reject the null hypothesis and we conclude that the GDP doesn’t influence the sale development of the Nokaragua country. The GDP may constantly increase but the sale may remain constant. Commodities bought from states are not influenced by the GDP.
H0: Prices of commodities from stores influence sales development
H1: Prices of commodities doesn’t influence sale development
The pvalue is 9.65 * 10^5 which is less than the level of significance which is alpha 0.05 hence we reject the null hypothesis and conclude that price of commodities in the store has no influence of the sale development. The price of commodities may be not friendly to the customers and hence they buy alternative brand of the commodity.
H0: Population development influences sale development
H1: Population development doesn’t influence the sale development
The pvalue 1.46 *10^7 is less than the level of significance 0.05 thus we reject the null hypothesis and conclude that the population development doesn’t influence the sale development. The population of people aged between 1565 years may constantly increase but alternatively the sale remains constant. The upcoming population may have no interest in the product in the stores.
Forecast model
The GDP influences 23.64% of the sales development, 3.22% price index contributes to model, population of person between 1565 years influences sale development by 48.32%, the survey score influences sales by 14.45%, advertisement of the stores influences the sale development model by 36.022% while the number of store and their strategic position influences the model by 31,.5%. The store should reconsider the prices of the commodities in the store to ensure that the sale development model increase the sale.
Federated Island1

Coefficients 
Standard Error 
t Stat 
Pvalue 
Lower 95% 
Upper 95% 
Intercept 
0 
#N/A 
#N/A 
#N/A 
#N/A 
#N/A 
GDP US$ 
0.205247077 
0.154118182 
1.331751219 
0.198698856 
0.117325985 
0.5278201 
Price index 
0.15767235 
0.052124715 
3.024905768 
0.006966417 
0.266770631 
0.048574 
Population 1565 
0.833930629 
0.30016399 
2.77825008 
0.011977372 
0.205680179 
1.4621811 
Survey score 
0.123452577 
0.075146765 
1.642819572 
0.116867278 
0.03383141 
0.2807366 
Advertisement 
0.627153351 
0.279416177 
2.244513394 
0.036902494 
0.042328573 
1.2119781 
Stores 
0.006708251 
0.232259441 
0.028882577 
0.977259465 
0.479416345 
0.4928328 
Statistical interpretation
H0: The GDP influences the sales development
H1: The GDP has no influence on the sale development
The pvalue 0.1986 which is greater than the level of significance 0.05 hence we fail to reject the null hypothesis and conclude that GDP influences the sale development. The sale development is highly influenced by the GDP as it increases the sales increase since the customers can afford much.
H0: Prices of commodities from stores influence sales development
H1: Prices of commodities doesn’t influence sale development
The pvalue 0.0069 is greater than the level of significance 0.05 hence we fail to reject the null hypothesis and hence conclude that price of commodities from the stores influence the sale development. The more accommodative the prices are the more the customers tend to buy from the store. The friendlier the prices are the more sales are made.
H0: Population development influences sale development
H1: Population development doesn’t influence the sale development
The pvalue 0.0119 is greater than the level of significance 0.05 hence we fail to reject the null hypothesis and conclude that the population development influences the sale development. The population increase the more they tend to buy more goods for their upkeep hence the sale develops. The larger the population the more units of sale are made.
Forecast model
The linear regression model is given by
The sales development is contributed by 20.54% GDP, price index influences 15.76%, population of persons aged 1565 years contributes 83.39%, survey score influences 12.34% of sale development, degree of advertisement development influences 62.72% of sale while number of store contributes to 0.67%of sale development.
The position and number of stores should be improving the model which will increase the sale development. The price negatively influences the sales; the improvement of prices will increase the sale.
Market place Sweden – Estimate of potential sales figures in 2016 and forecast to 2020
Market place Sweden
The country that is closely related to the newly opened Sweden is the Nokaraga. The two countries share the population rates high population doesn’t influence the sale development. The numbers of sales are number of units per person that they buy from stores. The Nokaragua is less likely the same as Sweden, the population increase doesn’t influence the sale development. The friendlier the prices are the more sales the store makes. The Nokaragua and Sweden share the factor that the goods bought are influenced by prices and their cost of living.
Estimates and potential sales for the Swedish market

Coefficients 
Standard Error 
t Stat 
Pvalue 
Intercept 
0 
#N/A 
#N/A 
#N/A 
Price index 
0.203868936 
0.140489115 
1.451136881 
0.160245349 
Population 1565 
1.697380091 
0.007241045 
234.4109285 
2.31595E40 
H0: Prices of commodities from stores influence sales development
H1: Prices of commodities doesn’t influence sale development
The table above is analysis of variance of price index and population of person 1565 years. The pvalue 0.1602 which is greater than level of significance 0.05 hence we fail to reject the null hypothesis and conclude that price of commodities from stores help in the development of the sales. The more convenient the prices the more sales are made.
H0: Population development influences sale development
H1: Population development doesn’t influence the sale development
The pvalue is less than the level of significance hence we reject null hypothesis and conclude that the population development doesn’t influence the sale development. Despite the increase in the population the sale development remain constant since only a given strata of population buy from the stores.
The Nokaragua is less likely the same as Sweden, the population increase doesn’t influence the sale development. The friendlier the prices are the more sales the store makes.
Forecast model
The GDP in Sweden is contributed by 20.38% of the prices while population contributes 69%. The model below can easily be used to predict future sales in Sweden
Sales US$= 0.20524*GDP0.1576*price index+0.8339*population+0.12345*survey score+0.62715*advertisement+0.0067*store
Survey score 
Advertisement 
Stores 
2.07 
2.97 
3.46 
2.07 
2.97 
3.46 
2.07 
2.97 
3.46 
2.07 
2.98 
3.46 
2.07 
2.98 
3.47 
2.08 
2.98 
3.47 
2.08 
2.98 
3.47 
2.08 
2.98 
3.47 
2.08 
2.98 
3.47 
2.08 
2.98 
3.47 
2.08 
2.99 
3.48 
2.08 
2.99 
3.48 
2.08 
2.99 
3.48 
2.08 
2.99 
3.48 
2.09 
2.99 
3.48 
2.09 
2.99 
3.49 
2.09 
3.00 
3.49 
2.09 
3.00 
3.49 
2.09 
3.00 
3.49 
2.09 
3.00 
3.49 
2.09 
3.00 
3.49 
2.09 
3.00 
3.50 
2.09 
3.00 
3.50 
2.09 
3.01 
3.50 
2.10 
3.01 
3.50 
2.10 
3.01 
3.50 
2.10 
3.01 
3.50 
2.10 
3.01 
3.51 
2.10 
3.01 
3.51 
2.10 
3.01 
3.51 
Conclusion
 The Board of Directors in the case Industria1 the sales are highly influenced by population of persons aged 1565 years hence they should increase the store to cater for all the customers.
 Industrial 1 the price indices which are influenced by inflation then the board should help making strategies to control.
 The Board of directors continues to increase advertisement and number of stores to allow convenience of customers.
 In the Nokaragua country, the GDP, advertisement, stores and survey score have value less than average hence the board of director should influence the different levels of advertisement, stores numbers will be increased and the different survey score will help improve the demands of customers.
 In the Federated Island, the population of contributes to sales as well as advertisements hence they should ensure that demands of customers through surveys are catered for as well advertisements reach the population. The number of stores should be increased to cater for the large population.
 In Sweden, the large population should be encouraged through the advertisement; the number of store should be catered to allow convenience. The survey score should ensure that customers ensure that they give their demand on products, services and labour. The GDP helps the sale development. The employment created will help in increasing the GDP though enforcing more personnel at labour force.
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