Price of Products in Different Supermarkets - Report Example

EXECUTIVE SUMMARY The main purpose of this report is basically to find out whether there is a difference in the prices that are charged on the basic staple basket in the in the different supermarkets in different states and the different locations within the country of Australian. This report has narrowed down the number of supermarkets to four; Coles/BI-LO, Woolworths, Independents and ALDI, three states; New South Wales, Queensland and Victoria and two major locations; the metropolitan capital city and other areas. The basic staple grocery items were 500 in number and ranged from bread, milk, sugar e.t.c. This report is required to assist The Australian Competition and Consumer Commission (ACCC) in determining whether the consumers are being exploited by the supermarkets in the various states within Australia. Descriptive data analysis on the supermarkets pricing COLES/BI-LO SUPERMARKETS Column1 Mean 2.5 Standard Error 0.102490008 Median 2.5 Mode 1 Standard Deviation 1.12272 Sample Variance 1.26050 Kurtosis -1.36670 Skewness 0.000 Range 3 Minimum 1 Maximum 4 Sum 300 Count 120 Coles supermarket was able to sell its products at the highest price in Victoria state which was 85.7 dollars followed by New South Wales state ad lastly Queensland state. Victoria State is due to the high demand for their products giving them a huge customer base that mandates the supermarket to charge the customers very high prices on the basic staples. However it’s not possible for Cole’s supermarket to charge the consumers high prices due to the low demand and low living costs that dictate the prevailing low prices on the basic staple products in New South Wales State and Queensland supermarkets. WOOLWORTHS SUPERMARKET Basing on the graph shown below, Woolworth supermarket charged the highest prices on its products in Queensland State compared to other states. This is because of the high demand of the products sold in Woolworth supermarket leading to the high prices charged by the supermarket in this state. This supermarket charged the lowest prices in the products that it sold in New South Wales State compared to the rest of the states due to the high supply of the products that forced the supermarket to lower the prices in order to make sales (Black, 2011). Independents supermarket Independents supermarkets sold its products in Queensland State at the highest price compared to the rest of the states. This is most likely due to the high demand on the products by the consumers and the cost incurred to get the products that made the suppliers to sell the products to the consumers at the highest price. The selling prices at Victoria state was lowest due to the stiff competition from the rest of the consumers and the high supply that forced the management to lower the prices (Freeman, 2010). Cumulative graph of the supermarkets in all over Australia From the graph above, Independents supermarket is the one that was selling the products at the highest price allover Australia followed by Coles, Woolworths and finally ALDI supermarket. The supermarkets that sell the basic staples at very high prices; Coles, Woolworths and independents are able to operate due to the high demand and customer preference to shop at their supermarkets. The high prices could also be due to the high living costs in their locations. ALDI supermarket is the supermarket selling the products at the lowest possible price in Australia, this could be due to high competition that forces the management to lower prices in order to increase their customer base and consider the poor in the society (Robert Stine, 2013). Question two Descriptive data analysis on the three states NEW SOUTH WALES STATE From the graph above, it’s clear that in New South Wales State, independents supermarket sold the basic stales at the highest prices followed by Coles, Woolworths and ALDI respectively. This could be due to high demand of products I the independents supermarkets making the management to hike the prices of the products. ALDI supermarket is charging low prices due to the high supply with the New South Wales state due to the many supermarkets that intensify the market competition making the consumers the dictators of the prices to prevail in the market. QUEENSLAND STATE In Queensland State, Independent supermarkets were selling the products at the highest price followed by Woolworths, Coles and ALDI supermarket respectively. In this state it’s clear that most consumers prefer buying their goods at Independents implying high demand making the suppliers to sell the products at very high prices while the ALDI supermarket sells the products at the lowest price due to the high competition from suppliers and the high supply that is higher than the demand in the market for the products making the consumers the price setters for the case of ALDI supermarkets (Tufféry, 2011). VICTORIA Relating to the graph above of the different pricings by the various supermarkets in Victoria State, it’s clear that Coles supermarket was selling the basic staples at the highest prices followed by the Independents supermarket, Woolworth supermarket and ALDI supermarket respectively. I this state ,it is clear that most consumer prefer shopping at Coles and Independents supermarkets giving them the power to charge very high prices on the commodities due to the high demand. ALDI supermarket charged lower prices in order to attract more customers most likely due to the high supply and stiff competition from the other supermarkets. Cumulative average prices by supermarkets in various supermarkets STATE TOTAL AVERAGE PRICES NEW SOUTH WALES 77.01 QUEENSLAND 77.64 VICTORIA 78.08 From the visual presentation above, it can be concluded that the prices of the basic staples was high in Victoria state at 78.10 dollars followed by Queensland state and lastly New South Wales state. The high prices in Victoria State could be due to high cost of living and high demand for the products making the supermarkets to highly price the products that are basic staple baskets since the high demand gives the suppliers power to exploit the consumers. The prices in the New South Wales state were very low compared to the prices in other states this is because of the lower living cost and there was also high supply of the basic staple products making forcing the supermarkets to set the prices lower so as to attract consumers to come and buy the products. QUESTION 3 Cumulative analysis of total sales by the supermarkets in all the three states From the graph above, the supermarkets in Victoria State set the highest price on the basic staples compared to the rest of the states. This could be due to the high demand for the products brought about by the high population that leads to rise in the living costs. Prices that were charged by the supermarkets in New South Wales State were moderate due to the match in the demand to the supply of the products in that state. However in Queensland State, the supermarkets charged very low prices on the products due to the low cost of living the high supply of the goods making the consumers the dictators of the prices to prevail on the products forcing the supermarkets to charge very low prices o the basic staples within Queensland supermarket. Question four; Hypothesis testing Step one; setting up Ho and Ha µ_f; there is no significant difference of the average prices µ_m; there is significant difference of the average prices Ha; Atleast one of the population isn’t same as the other Since there are more than two independent variables, we will use T test statistics. Step two; Deciding on the type of test Test statistics; T test, this is because there is a normal distribution and N being less than 30 and hence, we will use the T test statistics for our analysis Step three; Deciding on the level of significance Significance level; 5% The significance level is 0.05 df = n1 + n2 – 2 = 66 + 17 – 2 = 81,  With critical value from t table being1.664 Step four; the decision rule The verdict rule is that, we reject the null hypothesis when the P values are more than 5%. The calculated T value with the use of t test statistic is less than the critical value of 1.664, the null hypothesis is rejecting and conclusion might be there is significant difference of the average prices Step five; selecting a random sample and the calculation The P value critical is depicted in the following Test regression output. SUMMARY OUTPUT Regression Statistics Multiple R 0.866667 R Square 0.751111 Adjusted R Square 0.742222 Standard Error 0.258199 Observations 30 ANOVA   df SS MS F Significance F Regression 1 5.633333 5.633333 84.5 5.97E-10 Residual 28 1.866667 0.066667 Total 29 7.5         Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 0.2 0.149071 1.341641 0.190493 -0.10536 0.505359 X Variable 1 0.866667 0.094281 9.192388 5.97E-10 0.673541 1.059792 Step six; the conclusion From the above output, it can be observed that the P –values for the two price range for Woolworth and Coles depict a value of 0.1905 which is more than 0.05 and hence we reject the µ_f and concludes that there is significant difference of the average Prices (Freeman, 2010). In this regards, a company must therefore focus on being a price leader in competitive market in order to make supernormal profit and survive in a competitive market. Question five; How to test that there is a significant difference of average prices across three States We will undertake a regression analysis using the excel data analysis tool pack in order to get the P-values and compare with 5% significance level. Where the p values is more than the 5% significance level, we will reject the µ_f and concludes that there is a significant difference of average prices across three States Step one; setting up Ho and Ha µ_f; there is no significant difference of average prices across three States µ_m; there is a significant difference of average prices across three States Step two; Deciding on the type of test Test statistics; ANNOVA T test (Single factor test) Step three; Deciding on the level of significance Significance level; 5% Step four; the decision rule We reject the null hypothesis when the P values is more than 5% Step five; selecting a random sample and the calculation Anova: Single Factor SUMMARY Groups Count Sum Average Variance Column 1 40 59 1.475 0.255769 Column 2 40 60 1.5 0.25641 ANOVA Source of Variation SS df MS F P-value F crit Between Groups 0.0125 1 0.0125 0.048811 0.825723 3.963472 Within Groups 19.975 78 0.25609 Total 19.9875 79         Step six the decision rule The coefficient of X variables 1 is 0.8667 with a standard error of 0.09428 and p value of 0.8257 the implication is that we reject the µ.f (that there is no a significant difference of average prices across three States) since, the P-values is more than 0.005. Question n six; Testing whether there are differences in supermarket prices at different locations Step one; setting up Ho and Ha µ_f; there are no differences in supermarket prices at different locations µ_m; there are differences in supermarket prices at different locations Ha; At least one of the population isn’t same as the other Since there are more than two independent variables, we will use T test statistics. Step two; Deciding on the type of test Test statistics; T test, this is because there is a normal distribution and N being less than 30 and hence, we will use the T test statistics for our analysis Step three; Deciding on the level of significance Significance level; 5% The significance level is 0.05 df = n1 + n2 – 2 = 66 + 17 – 2 = 81,  With critical value from t table being1.664 Step four; the decision rule The decision rule is that, we reject the null hypothesis where the p values is more than 0.05. the conclusion reached in this regards will accept there alternative hypothesis and conclude that there are differences in supermarket prices at different locations Step five; selecting a random sample and the calculation The P value critical is depicted in the following Test regression output. SUMMARY OUTPUT Regression Statistics Multiple R 0.851064 R Square 0.724311 Adjusted R Square 0.717056 Standard Error 0.269014 Observations 40 ANOVA   df SS MS F Significance F Regression 1 7.225 7.225 99.83636 3.49E-12 Residual 38 2.75 0.072368 Total 39 9.975         Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 0.2 0.134507 1.486913 0.145289 -0.07229 0.472295 X Variable 1 0.85 0.08507 9.991815 3.49E-12 0.677786 1.022214 Step six; the conclusion From the output above, it is evident that the p-values is 0.1453 which is more than 0.05 and thus we reject the null hypothesis and concludes that there are differences in supermarket prices at different locations (Tufféry, 2011). Question seven testing whether there is significant difference of average prices of ALDI stores in three states Step one; setting up Ho and Ha µ_f; there is no significant difference of average prices of ALDI stores in three states µ_m; there is significant difference of average prices of ALDI stores in three states Step two; Deciding on the type of test Test statistics; ANNOVA T test (Single factor test) Step three; Deciding on the level of significance Significance level; 5% Step four; the decision rule We reject the null hypothesis when the P values is more than 5% Step five; selecting a random sample and the calculation Anova: Single Factor SUMMARY OUTPUT Regression Statistics Multiple R 0.816497 R Square 0.666667 Adjusted R Square 0.625 Standard Error 0.316228 Observations 10 ANOVA   df SS MS F Significance F Regression 1 1.6 1.6 16 0.00395 Residual 8 0.8 0.1 Total 9 2.4         Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 0.2 0.316228 0.632456 0.5447 -0.5292 0.9292 X Variable 1 0.8 0.2 4 0.0039 0.3388 1.2612 Step six; Decision Rule From the above output, at 5% significance level, it can be observed that p values is 0.5447 which is more than 0.05 and thus we conclude that the µ_f be rejected and accept the µ_m which states that there is significant difference of average prices of ALDI stores in three states (Tufféry, 2011). Conclusion and Recommendation From the above analysis of the price of goods for Woolworth and Cole’s supermarket, it can be observed that the price of the product is different based on state, location and supermarket. The implication is that there is a stiff competition in supermarket which would lead to rivalry, exit of other supermarket due to fierce competition and thus, to survive in this kind of competitive market, there is need to ensure that the product is acceptable in the market in term of pricing, branding and taste and preference. Bibliography Black, K. (2011) Business Statistics: For Contemporary Decision Making - Page 296, London. Freeman, E. (2010) Stakeholder Theory: The State of the Art, London: Cingage Learning. Freeman, E. (2010) Stakeholder Theory: The State of the Art - Page 330. Robert Stine, ‎.F. (2013) Statistics for Business: Decision Making and Analysis, New York. Tufféry, S. (2011) Data Mining and Statistics for Decision Making, New York: Cingage learning. 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