BORA analysis Essay Example

  • Category:
    Statistics
  • Document type:
    Essay
  • Level:
    Undergraduate
  • Page:
    3
  • Words:
    2085

BRAND ORIGIN RECOGNITION ACCURACY

1. SUMMARY AND DESCRIPTION OF THE DISTRIBUTION OF VARIABLES.

The purpose of this report is to analyze and review the research on Brand Origin Recognition Accuracy (BORA). According to Mohammed (2011) this is used in marketing literature and consumer perception.

Analyze UK residents on the actual origin of different products or brands and how they influence consumer behavior as stated Ramsey (2009). In this survey results, consumers well know which brands where from the UK, the one of non UK origin, and the one in which consumers know which country specifically came from (BORA country).

This information is important stating the influences on product attributes, quality and consumer behavior.

BORA an analysis undertaken by questionnaire on the UK residents, requiring them to state if they are familiar with the origin of different brands.

The BORA statistic contains results from a survey of UK residents, who were asked to identify the country of origin of 18 well-known brands. The data in the file are of 150 respondents to the survey. Figures identified for number of UK brands identify as being of UK origin, number of non UK brands correctly identified of non UK origin and the number of non UK brands for which the country of origin was specified. These variables are labelled respectively as BORA UK, BORA non UK and BORA country.

Survey results also contain values of consumer cosmopolitan score (COSMO)

Spread of data is distributed differently within variables of a data set. The information provided is essential in summary and conclusion on various measures on the relevant data.

The frequency table describe consumer perception of different brands and origin of this product has been shown by Cardoso and Francisco (2011). The distribution of a variable is the number of times an outcome will occur in a number of experiments. The data of BORA UK states the number of brands that different respondents (150) thought are the UK, through a series of 18 brands.

The focus to this analysis is to develop a frequency distribution. This suggested same score that fall in the same range of respondents among the 150.Frequency distribution table for the discrete variables.

The survey resulted to both male and female. The total male survey was 67 out of a total of 150 respondents. The total gender survey that identified the product brand origin was 965.The total male survey results of BORA UK was 424.

Frequency distribution table

frequency

relative frequency

The variable recorded was of sex as illustrated in the frequency distribution above. The last table column consists of the relative frequency, which are computed by dividing the frequency of the males by the total sample size (i.e. 424/965) and expressing as percentage.

The summary of survey conducted for 150 respondents, male and female. The figures identified for the number of brand on no UK origin. The total male survey was 62 out of a total 150 respondents. The total gender survey identified non UK brand origin was 1098.

Males total count was 477.Therefore the female count was 621.We summarize this data using frequency distribution tables for sex as shown by the table below.

Frequency distribution table for sex non UK brand origin

frequency

relative frequency %

Consumer cosmopolitanism

Marketing literature proves the position of consumer perception on local or foreign brands. However, further investigation of Daniel et al (2004) why consumer might consider foreign products over local. Consumer cosmopolitan is introduced as an attribute that explains the preference. The results below highlight the position of consumer measures.

Frequency distribution table consumer cosmopolitan

frequency

relative frequency

2. DIFFERENCE IN AVERAGE BORA BETWEEN MALE AND FEMALE

Findings of the research survey are categorically classified. The data sets consist of a frequency distribution between the categories. The population proportion of BORA was between the male and female gender. These are two population proportion and a variable of interest analyzed.

It is important to compare the proportion of UK BORA, non UK BORA, and BORA country of the two population. Males and females were asked about their perception of actual origin of different products or brands and how this influence consumer behavior.

The total male survey was 67 out of a total 150 respondents. This figure produce a relative frequency of 43% where as 56.06% of the UK BORA. This estimates the population proportion of male gender who thought that this brands where of UK origin. A higher percentage than that of the females noted.

The gender was on male and female and sample observed on male was m1 and sample observed on women was m2. This proportions can be used for statistical inference. The total sample population was 150 respondents both male and female. Test is the population from which the respondent is selected, if there were a difference in average BORA between men and women. male population was 62 out of the 150 respondents, whereas the female population was 83 out of total of 150 respondents.

THE METHODS EMPLOYED IS HYPOTHESIS TESTING.

Conduct a test procedure known as hypothesis testing.

Hypothesis testing the difference between averages of the male and female. This approach involves a four-step process

(1). state the hypothesis

(2). formulate an analysis plan.

(3) Analyze sample data

(4) Interpret results.

Sayed et al. (2011) state the hypothesis be as either null hypothesis or an alternative hypothesis. They are mutually exclusive, if one is true and the either is false. The difference between the average of BORA male and the average of BORA women.

Null hypothesis u1-u2=d

Alternative hypothesis u1-u2≠d

We conduct a two-tailed test.

Create an analysis procedure, there are important aspects that should be incorporated to accept or reject the null hypothesis. Using a significant level of 0.05. The test method employed is the

BORA UK & BORA non UK

t-Test: Two-Sample Assuming Unequal Variances

6.422819

7.308725

Variance

2.678124

1.633775

Observations

Hypothesized Mean Difference

0

-5.20771

P(T<=t) one-tail

1.85E-07

t Critical one-tail

1.650314

P(T<=t) two-tail

3.71E-07

t Critical two-tail

1.968472

Two sample t-test to evaluate the difference between the computed averages in the sample is different from the hypothesized difference between the means.

The analysis on the test statistics should be able to give you standard error, degrees of freedom, test statistics and the p-value.

P-value, probability value of the computed statistics against the test statistics.

Conclusion;

If the p-value significant to the significance level, we accept the null hypothesis. We reject the null hypothesis if the p-value is less than the significance level.

The average between male and female, there is a significant difference between the mean averages of the male and female therefore we reject the null hypothesis and accept the alternative hypothesis.

Q3. Determine whether there is evidence that, in the population from the respondents selected, the average BORA for the UK brand was different from that for the non UK brand. Addressed separately for both male and female.

The average BORA for the UK brand from the male survey was and the average from that of the non UK brand of the male was. Report should justify if there was a significant difference of the averages between UK brand and non UK brands. In this analysis, we use the methodology of hypothesis testing for difference between two population means.

We conduct a two-sample z-test, which conclude if the two population means are different or indifferent.

A series of steps is involved in comparing two independent means.

  1. Identify the null hypothesis and alternative hypothesis. Are the means of UK brands and non UK brands of males and females separately different? We state the null hypothesis Ho u1-u2=0 and the alternative hypothesis Ha u1-u2≠0.

  2. Compute a test statistics, conduct a t test as shown by the table below.

The table above states the statistics with regards to the standard error which is manually determined by the standard deviation. Degrees of freedom can be computed manually too, but the regression analysis table indicates their degrees of freedom

  1. P-value is determined in the t-test of the test statistics. If the p-value is significant to the significance level (0.05), we accept the null hypothesis, if the p-value is less than the significance level.

t-Test: Two-Sample Assuming Unequal Variances

6.422819

7.308725

Variance

2.678124

1.633775

Observations

Hypothesized Mean Difference

0

-5.20771

P(T<=t) one-tail

1.85E-07

t Critical one-tail

1.650314

P(T<=t) two-tail

3.71E-07

t Critical two-tail

1.968472

Conclusion;

The average between UK brand and non UK brands of the males, there is a significant difference between the means. Therefore, we reject the null hypothesis, meaning we accept the alternative hypothesis that both means are indifferent.

The average UK brands and non UK brands of the females, there is a significant difference between the means. Therefore, we reject the null hypothesis, state the alternative hypothesis is correct, that both means are indifferent.

Examine the relationship of two population between COSMO’ and BORA UK and BORA non UK and COSMO on the other hand. Do the two variables share a relationship with each other?

Statistical inference concluded with multiple regression. The population statistics are computed and the relationship between the COSMO and BORA UK identified.

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.321798

0.103554

Adjusted R Square

0.097456

Standard Error

1.554711

Observations

Significance F

Regression

41.04485

41.04485

16.98084

6.28E-05

Residual

355.3176

2.417126

396.3624

Coefficients

Standard Error

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

4.084372

0.581594

7.022717

7.49E-11

2.935006

5.233738

2.935006

5.233738

0.100731

0.024445

4.120782

6.28E-05

0.052423

0.149039

0.052423

0.149039

In this survey consumer cosmopolitanism is view to be in the same relationship as both BORA UK and COSMO aspect states why consumer prefer foreign products over local products. It is introduced as an attribute that explains the preference. The results above highlight the position of consumer perception. Why consumers consider attributes of foreign product over their UK local brand products.

The main objective of conducting multiple regression is to understand the relationship between independent and dependent variables. In our case BORA UK and COSMO.

The relationship between COSMO and BORA UK, and between COSMO and BORA non UK. Analyzed using multiple regression in the data analysis tool pack.

They are three categories in the regression output i.e. regression statistics, nova and Regression coefficient. This states that relevant data analyzed from UK residents on their brand origin recognition and the Cosmo analysis, where corresponsive.

Interpret the results;

The measures are of certainty R²=0. 103554.The correlation between the two variable is 0.3217, this is R squared.

The standard error is the estimate of standard deviation of the error 1.55471.R²=0.103554 illustrates that 10.35% of the variation between two variables.

Interpreting Anova table, this is known as the analysis of variation. There is a strong relationship between the two variables. This is also evident in the COSMO and BORA non UK regression analysis, as shown in the table below.

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.057757

0.003336

Adjusted R Square

-0.00344

Standard Error

1.280391

Observations

Significance F

Regression

0.806597

0.806597

0.492007

0.484142

Residual

240.9921

1.639402

241.7987

Coefficients

Standard Error

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

6.980912

0.478975

14.57468

2.46E-30

6.034345

7.927479

6.034345

7.927479

0.014121

0.020132

0.701432

0.484142

-0.02566

0.053905

-0.02566

0.053905

Conclusion;

A number of residents stated foreign products having high quality attributes. This where the reasons on where these products where their preferences and choice,

The results of the research state that UK residents were able to recognize the origin of brands from UK better compared to the products from non UK. This is a result of various factors from economic factors, demographics such as age, gender sex, social status and amount of information. The use of the World Wide Web has influenced a number of residents to recognized foreign brands.

The consumer cosmopolitanism has brought about cultural integration and diversity. People from different cultures embrace and interact with different communities and their ways of life.

Women tend to interact more to foreign culture compared to men. Survey conducted suggest that UK [ CITATION Ami11 l 1033 ]female’s resident prefer foreign brands more than the males.

Works Cited

Cardoso, F. a. a. B., 2011. The importance of products attributes on Brand loyalty development. internal journal for Business RESEARCH, 11(1), p. PG176.

Daniel Hall, F. P. a. R. O., 2004. Histograms. Machine visions & Application, 16(1), p. 14.

Mohammed, A., 2011. Consumer brand origin recognition attributes. issue 8 ed. s.l.:journal of applied science research.

Monsey Seyed, M. s. ,. S., 2011. Consumer Brand Origin Recognition Accuracy. Journal of Applied science research, 7(8), p. 1435.

Ramsey, D., 2009. Hypothesis testing for means & proportions. 2nd ed. Boston: Boston University school.