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Data Analysis

The purpose of this assignment is to explore the under-filling issue highlighted by the media in case of tuna can products all over the Australian market. This study was performed for a consumer interest group who decided to investigate this issue and identify the current demand for this product. Accordingly the survey was done for two brands named brand A and brand B over the two months period. A total 645 customers feedback was collected. However, from this population a sample of 100 customer responses were taken into account for analysis. In order to collect the sample, the group of analyst has used random sampling technique. Firstly, they used excel RAND() function to generate random number for each of the 645 responses. Subsequently, the random numbers were sorted and first 100 were chosen as the sample for this study. The analysis has been done in three phase. The first section of this report demonstrated basic analysis, whereas the second and third phase covered intermediate level of analysis and advance scenario analysis respectively.

Section A: Basic Analysis

Firstly, the analyst group has identified the proportion purchased of two brands. The same has been mentioned in the below table and visualised through below graph. According to this findings, the popularity for brand B is almost double to brand A.

 Brand Sample Proportion A 37 B 63 Grand Total 100

If the average weight of two brands are taken into consideration, then it can be found from the below table that brand A is comparatively better than brand B in terms of under-filling issue. In fact the average weight is indicating more than standard volume than the label volume. However, the spread is also high for brand A. Therefore, there is more deviation n weight for brand A product than brand B.

 Brand A Brand B Minimum weight 90.5 87.1 Maximum weight 113 106.9 Range 22.5 19.8 Average weight 101.7 98.3 Standard deviation 4.7 4.3

The analyst group has performed frequency distribution of both the brands as mentioned below. The level volume is 100 gm specified by the consumer interest group. Therefore, according to this table, all those cans can be segregated as under-filled where the weight reduced to 98gm or less. Hence, it can be concluded that 21.62% of brand A and 41.27% of brand B is under-filled.

 Class Frequency Relative Frequency Cumulative Relative Frequency (%) (%) A B A B A B 86 to 90 0 3 0.00% 4.76% 0.00% 4.76% 90 to 94 2 8 5.41% 12.70% 5.41% 17.46% 94 to 98 6 15 16.22% 23.81% 21.62% 41.27% 98 to 102 11 24 29.73% 38.10% 51.35% 79.37% 102 to 106 11 12 29.73% 19.05% 81.08% 98.41% 106 to 110 5 1 13.51% 1.59% 94.59% 100.00% More than 110 2 0 5.41% 0.00% 100.00% 100.00% Total 37 63 100% 100%

It has seen from the below mentioned table as well as graph that the under-filling behaviour is significantly different for these two brands. While the analysis indicates a less number of respondents agrees with under-filling aspect of brand A; there is almost 50% respondents has mentioned that they found under-filling can from brand B products.

 Cross classification table by frequency Underweight? Total Yes No Brand A 8 29 37 B 27 36 63 Total 35 65 100

## Section A: Basic Analysis

 Cross classification table by brand total relative frequency Underweight? Total Yes No Brand A 8.00% 29.00% 37.00% B 27.00% 36.00% 63.00% Total 35.00% 65.00% 100.00%

Section B: Intermediate Level Analysis

 Discount offered Proportion of ALL customers who said they will buy the new product x Y 0% 12% 5% 23% 10% 31% 15% 37% 20% 44% 25% 51%

From the above graph, it has seen that the intercept value is 0.1414. This indicates that if discount offered to the customer become zero, then also there will be at least 14.14% proportion of customers who will purchase these products.

Again, the co-efficient of x value, 1.5086 indicates that any changes in discount offered will increase the market share by 1.5086 times of discounted value beyond 14.14%.

Finally, the R squared value is 0.9897, which indicates that there is almost perfect positive association between discount offered and proportion of customer.

Given, y=1.5086x+0.1414

Here, y = 25%

Therefore, 0.25 = 1.5086x + 0.1414

Or, X = (0.25-0.1414)/ 1.5086 = 0.0720 = 7.20%

 Discount offered Proportion of customers who said they will buy the new product Brand A Brand B x yA yB 0% 0 12 5% 10 13 10% 10 20 15% 10 26 20% 15 27 25% 17 32

The above scatter plot is representing the association between discount offered on the new product (NT tuna) and the proportion of each brand’s customers who said that they will buy the new product if they are offered the stated discount. From this, it can be said that customers of brand A is more loyal to the brand as the increase or decrease in discount influence the market proportion lesser than brand B.

From this, it can also be concluded that if there is no discount offered then also the market share will be 3.19% for brand A and 11.095% for brand B.

From the calculations done in section 1, it can be said that the number of customer who will purchase brand A product is 37 and the same for brand B is 63. Hence, the proportion of customer for brand A = 37/100 = 37% and for B = 63/100 = 63%.

 Confidence Interval for the proportion Data Sample Size 10000% Count of Successes 3700% Confidence Level 95% Intermediate Calculations Sample Proportion 0.37 z Value 1.959963985 Standard Error of the Proportion 0.048280431 Margin of Error 9% Assumptions: n.p=37, n.q=63 MET Confidence Interval Interval Lower Limit 28% Interval Upper Limit 46%

The above mentioned table and graph is showing 95% confidence interval for brand A. from this, it can be said that there is 95% chance that the minimum of 28% and maximum of 46% customer will purchase brand A.

 Confidence Interval for the proportion Data Sample Size 10000% Count of Successes 6300% Confidence Level 95% Intermediate Calculations Sample Proportion 0.63 z Value 1.959964 Standard Error of the Proportion 0.04828 Margin of Error 9% Assumptions: n.p=63, n.q=37 MET Confidence Interval Interval Lower Limit 54% Interval Upper Limit 72%

The above mentioned table and graph is showing 95% confidence interval for brand B. from this, it can be said that there is 95% chance that the minimum of 54% and maximum of 72% customer will purchase brand B.

 Confidence Interval for the mean Data Sample Standard Deviation 4.7 Sample Mean 101.7 Sample Size 37 Confidence Level 0.95 Is Pop StDev known? Y/N N Intermediate Calculations Standard Error of the Mean 0.77267524 Degrees of Freedom 36 t Value 2.028094001 Margin of Error 1.56705802 Confidence Interval Interval Lower Limit 100.1 Interval Upper Limit 103.3

The above mentioned table and graph is showing 95% confidence interval of average weights for brand A. from this, it can be said that there is 95% chance that the average weight will stay in between 100.1 to 103.3.

 Confidence Interval for the mean Data Sample Standard Deviation 4.3 Sample Mean 98.3 Sample Size 63 Confidence Level 0.95 Is Pop StDev known? Y/N N Intermediate Calculations Standard Error of the Mean 0.541749 Degrees of Freedom 62 t Value 1.998972 Margin of Error 1.082941 Confidence Interval Interval Lower Limit 97.2 Interval Upper Limit 99.4

The above mentioned table and graph is showing 95% confidence interval of average weights for brand B. from this, it can be said that there is 95% chance that the average weight will stay in between 97.2 to 99.4.

 Hypothesis Test for µ Hypotheses Null Hypothesis H0: µ = 100 Alternative Hypothesis HA: µ <> 100 Test Type Two Level of significance alpha α set to: 0.05 Critical Region Degrees of Freedom 36 Lower Critical Value -2.028094001 Upper Critical Value 2.028094001 Sample Data Sample Standard Deviation s 4.7 Sample Mean x bar 101.7 Sample Size n 37 Is Pop StDev known? Y/N N Standard Error of the Mean 0.77267524 t Sample Statistic 2.200148149 p-value from the t distribution 0.034298701 Hypothesis test decision: Reject the Null Hypothesis

Here, the analyst group has performed one sample t test for mean in order to investigate whether the average weight of brand A product is 100gm or not.

The null hypothesis for this study considered as H0: average weight of brand A product is not equal to 100gm and the alternative hypothesis is considered as H1:  average weight of brand A product is equal to 100gm

Since, the p value is less than 0.05 at 5% confidence level, it can be concluded that null hypothesis will be rejected. That is, average weight of brand A product is equal to 100gm.

 Hypothesis Test for π Hypotheses Null Hypothesis H0: π ≥ 0.2 Alternative Hypothesis HA: π < 0.2 Test Type Lower Level of significance alpha α set to: 0.05 Critical Region Critical Value -1.644853627 Sample Data Sample Size 100 Count of 'Successes' 27 Sample proportion, p 0.27 Standard Error 0.04 z Sample Statistic 1.75 p-value 0.959940843 Assumptions: n.π=20, n.π=80 MET Hypothesis test decision: Fail to reject the Null Hypothesis

Here, the analyst group has performed one sample z test for proportion in order to investigate whether the brand B’s producer claimed that less than 20% of their cans are under-filled or not.

The null hypothesis for this study considered as H0: average under-filled product proportion is greater than or equal 20% and the alternative hypothesis is considered as H1:  average under-filled product proportion is less than 20%.

Since, the p value is greater than 0.05 at 5% confidence level, it can be concluded that null hypothesis will be accepted. That is, average under-filled product proportion is greater than or equal 20%.

Thus, it can be said that the study has analysed a list of aspect to understand the current market scenario and explore the possibilities that will help the consumer group to design their product.

The survey method used in this study is also appropriate enough to monitor the movement of customers due to external influence like discount or other competitor product.

The random sampling method used for this study is also effective as it provided an effective outcome. However, the selection of location only in Northland Shopping centre on multiple days will be a concern for the consumer group as it will not be treated as the true representative of Australian market.

Anderson, D., Sweeney, D. and Williams, T., 2014. Modern business statistics with Microsoft Excel. Nelson Education.

Anderson, D.R., Sweeney, D.J., Williams, T.A., Camm, J.D. and Cochran, J.J., 2016. Statistics for business & economics. Nelson Education.

David, R.A., Dennis, J.S. and Thomas, A.W., 2015. Modern Business Statistics with Microsoft Excel.

Freed, N., Bergquist, T. and Jones, S., 2014. Understanding business statistics. John Wiley & Sons.

Lee, N. and Peters, M., 2015. Business statistics using EXCEL and SPSS. Sage.

Cite This Work

My Assignment Help. (2022). Exploring Under-Filling Issue In Tuna Can Products: Data Analysis And Potential Demand Essay.. Retrieved from https://myassignmenthelp.com/free-samples/bus1ban-business-analytics/the-demand-for-a-new-product-file-A9411C.html.

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My Assignment Help (2022) Exploring Under-Filling Issue In Tuna Can Products: Data Analysis And Potential Demand Essay. [Online]. Available from: https://myassignmenthelp.com/free-samples/bus1ban-business-analytics/the-demand-for-a-new-product-file-A9411C.html
[Accessed 15 September 2024].

My Assignment Help. 'Exploring Under-Filling Issue In Tuna Can Products: Data Analysis And Potential Demand Essay.' (My Assignment Help, 2022) <https://myassignmenthelp.com/free-samples/bus1ban-business-analytics/the-demand-for-a-new-product-file-A9411C.html> accessed 15 September 2024.

My Assignment Help. Exploring Under-Filling Issue In Tuna Can Products: Data Analysis And Potential Demand Essay. [Internet]. My Assignment Help. 2022 [cited 15 September 2024]. Available from: https://myassignmenthelp.com/free-samples/bus1ban-business-analytics/the-demand-for-a-new-product-file-A9411C.html.

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