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                                 The data analysis on the potential customers

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                                 The data analysis on the potential customers

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The data analysis on the potential customers

This particular study aims to carry out some essential data analysis on the data of 500 customers on the tablet company. The examination or the data will be done on the SPSS file concerning the potential customers who are believed to be the target of the Tablet company. The analyses of the collected data will be done based on the T-test analysis, the ANOVA test, the correlation between two sets of variables, and the descriptive statistics.  The variable within the population of the 500 potential customers of the Tablet company is made up of different measures such as the nominal, the ordinal, and the scale (Plonsky, 2015). The ordinal values generally involve the numeric values or figures, while the nominal consists of the qualitative data such as the names of places and other related elements.

The correlation analysis is essential as it enables one to find a significant relationship between the two variables under study. The correlation values usually range from negative 1 to positive (-1 to 1) whereby when the value of correlation is below 0.5, it means that there is a significant relationship between the two variables under study (Ustaoglu, 2020). On the other hand, when the value of the correlation is above 0.5, then it indicates that there is a significant relationship between the two variables under study. Descriptive analysis of the collected data on the SPSS will also be done, which involves the description of data using the population parameters (Amrhein, 2019). The population parameters will mainly include quantities such as the mean, the range, the percentage, and other related quantities.

Now that so many variables among the 500 variables, the variables of interest to carry out this particular study will be the sex, marital status, age, sex, degree, the companies, and the banks. Therefore the output of the data concerning the 500 potential customers on the SPSS file are as follows:

Figure 1: The T-test distribution between sex and the marital status,

 

Group Statistics
MARITAL STATUSNMeanStd. DeviationStd. Error Mean
SEXUAL ORIENTATIONMARRIED1912.98.144.010
WIDOWED303.00.000.000

 

Independent Samples Test
Levene’s Test for Equality of Variancest-test for Equality of Means
FSig.tdfSig. (2-tailed)Mean DifferenceStd. Error Difference95% Confidence Interval of the Difference
LowerUpper
SEXUAL ORIENTATIONEqual variances assumed2.656.105-.797219.426-.021.026-.073.031
Equal variances not assumed-2.016190.000.045-.021.010-.041.000

 

Table 2: The ANOVA table showing the distribution of age respondents and sexual orientation.

 

ANOVA
Sum of SquaresdfMean SquareFSig.
AGE OF RESPONDENTBetween Groups280.060393.353.302.824
Within Groups74483.507241309.060
Total74763.567244
SEXUAL ORIENTATIONBetween Groups.0563.019.410.746
Within Groups9.645210.046
Total9.701213

 

As per the ANOVA table above, there is a value of 0.824, which is above 0.5; hence there is a strong significant relationship between the age of the respondents and the sexual orientation.

Table 3: The correlation relationship between the R confidence in major companies and the confidence in banks and the other financial institutions.

Correlations
R CONFIDENCE IN MAJOR COMPANIESCONFID IN BANKS & FINANCIAL INSTITUTIONS
R CONFIDENCE IN MAJOR COMPANIESPearson Correlation1.371**
Sig. (2-tailed).000
N338336
CONFID IN BANKS & FINANCIAL INSTITUTIONSPearson Correlation.371**1
Sig. (2-tailed).000
N336341
**. Correlation is significant at the 0.01 level (2-tailed).

The Correlation relationship between the two variables in table 3 shows a value of 0.371, which is below 0.5; therefore, there is no relationship between major companies and banks and other financial institutions.

Table 4: The frequency table for the marital status of the respondents.

 

MARITAL STATUS
FrequencyPercentValid PercentCumulative Percent
ValidMARRIED22545.045.045.0
WIDOWED397.87.852.8
DIVORCED7615.215.268.0
SEPARATED163.23.271.2
NEVER MARRIED14428.828.8100.0
Total500100.0100.0

As per the frequency table in table 4 on the marital status, the married people are the leading with the highest percentage distribution of 45%, which is also the model at the frequency of 225. Therefore the married people are also potential customers to the Tablet company.

 

 

Table 5: The frequency table for the R confidence in the major Companies

 

R CONFIDENCE IN MAJOR COMPANIES
FrequencyPercentValid PercentCumulative Percent
ValidA GREAT DEAL6613.219.519.5
ONLY SOME20641.260.980.5
HARDLY ANY6613.219.5100.0
Total33867.6100.0
MissingIAP15531.0
DK71.4
Total16232.4
Total500100.0

As per the distribution of the frequency table of the major companies in table 5, the highest percentage is working on Total at 67.6%, which is also the model at the frequency of 338, and therefore these are the potential customers in the study.

 

Table 6: The descriptive statistics of sexual orientation.

 

Descriptive Statistics
NMinimumMaximumMeanStd. Deviation
SEXUAL ORIENTATION428132.95.273
Valid N (listwise)428

As per the distribution of the data concerning the sexual orientation in table 6, there is a mean of 2.95 and a standard deviation of 0.295.

 

Table 7: Descriptive statistics on the marital status of the respondents.

 

Descriptive Statistics
NMinimumMaximumMeanStd. Deviation
MARITAL STATUS500152.631.712
Valid N (listwise)500

As per the distribution of the data in table 7, there is a population size of 500, and the mean of the marital status is 2.63.

 

Table 8: Descriptive statistics on family income.

 

Descriptive Statistics
NMinimumMaximumMeanStd. Deviation
FAMILY INCOME IN CONSTANT DOLLARS44638317871264282.6654229.003
Valid N (listwise)446

 

As per the distribution of the data in table 8, there is a population size of 446 and the mean of the family income 64282.66. Therefore, in the conclusion of all these forms of analysis concerning the study’s objective, the married people and then those who work at Total are the most potential customers to the Tablet company.

                                                      Reference

Amrhein, V., Trafimow, D., & Greenland, S. (2019). Inferential statistics as descriptive statistics: There is no replication crisis if we don’t expect replication. The American Statistician73(sup1), 262-270.

Plonsky, L. (2015). Statistical power, p values, descriptive statistics, and effect sizes: A” back-to-basics” approach to advancing quantitative methods in L2 research. Routledge.

Ustaoglu, A., Kursuncu, B., Alptekin, M., & Gok, M. S. (2020). Performance optimization and parametric evaluation of the cascade vapor compression refrigeration cycle using Taguchi and ANOVA methods. Applied Thermal Engineering, 115816.

 

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