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Data Editing and Descriptive Analysis Techniques

Student’s Name

Institutional Affiliation

Course Number

Instructor’s Name

Due Date
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Data Editing and Descriptive Analysis Techniques

Description of the data editing techniques used

Duplicate data entry

The duplicate data editing technique was used to determine the possibility of duplicate

data in the data collected. Each respondent was given a specific identity to ensure no two

respondents had overlapping data. Each respondent’s data was recorded in a specific column to

minimize the chances of confusion between different respondents. All the entries of the research

questions were cross-checked against respondents to ensure that they were relevant to the

objectives of the research.

Outliers

The data were checked for outliers among the responses given by respondents. Outliers

exist when one answer provided is way far from the range of the other responses. For instance, if

all respondents are recording 100,000 then one respondent records 100, the data must be edited

to ensure that it meets all the standards of the research. All the data passed the test and no

outliers were detected.

Logical inconsistencies

Based on previous reports of the information being investigated, logical inconsistencies

can be detected. The data was edited against the existing records of related data. Where logical

inconsistencies were detected, appropriate action was taken to ensure that data was relevant.

Validity and completeness of data

The data was edited to ensure it was complete as per the requirements of the research.

This editing aspect was checked to ensure that all respondents answered their questions

according to the format provided. The data was edited to ensure all questions asked were

promptly answered to ensure that the provided data was relevant to the research process. The

data was also checked to ensure that all responses were valid and that they sought to address the

questions asked in the survey.

Explanation of the results for each variable in the spreadsheet using descriptive analysis

techniques. Use appropriate tables and charts for each variable.

Products Shopped online Number of respondents Percentage

Electronics 4 40

Clothes 3 30

House Goods 1 10

Food 2 20

Total 10 100

Table of preferred products shopped online

For products shopped online electronics were the most shopped at 40%. The least

shopped products were house goods at 10% while clothes and food were shopped at 30% and

20% respectively.

Preferred furniture color Number of Respondents Percentage

Grey 3 30

Blue 1 10

Brown 2 20
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Black 2 20

White 2 20

Total 10 100

Table of preferred furniture color

The most preferred furniture color was grey at 30% while the least favored color was

blue at 10%. Brown, Black, and White had the same preference level at 20%

Respondents confidence level on online pre-payments

Risky Confident Opposed

Respondents did not prefer online pre-payments since 50% of them were opposed to the

concept. Only 30% were confident about the concept while 20% considered it risky
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Frequency of online shopping

Frequent Rare

Respondent’s frequency of online shopping was 60% for those who graded their level as

frequent. 40% of respondents considered themselves rare online shoppers.

Feelings about eco-packaging

Good Bad

An overwhelming majority of the respondents considered eco-packaging a good idea and

favored its use at 90% while 10% of the respondents thought it was a bad idea.

Online shopping satisfaction

Satisfied Not satisfied

The satisfaction level of online shopping was slip even between those who considered

themselves satisfied and those who did not feel satisfied with it.

Explanation of the results for each inferential analysis technique to determine

generalizations from the sample to the population. Describe how hypothesis testing was

used in this data collection and how it advances the accomplishment of the research

objectives.

Out of the four available online shopped products, 40 percent of the respondents

preferred electronics. It is therefore right to conclude that online shoppers prefer shopping online

products more than any other products. Online shoppers have various preferences on the color of

online furniture to purchase. The five most common furniture colors were split almost evenly

among the respondents indicating that there is no clear choice to define that choice. From the

data it is right to conclude that most respondents do not prefer online pre-payments since 50% of

them opposed the concept. Only 30% of the respondents thought that online pre-payments were a

good idea indicating that most customers prefer paying for their packages at the points of

delivery even if they have to shop online. Most respondents feel positive about eco-packaging at

90%. Therefore, it is right to conclude that most online shoppers care about sustainability and

environmental protection. Regarding satisfaction, it is right to conclude that half of the online

shoppers are satisfied with the services while half are not satisfied.

Explanation of the results for each inferential analysis technique to determine differences

between groups in the sample, or the percentages or means of two or more variables (two-

sample test of means, Chi-square test, or ANOVA). Describe how hypothesis testing was

used in this data collection and how it advances the accomplishment of the research

objectives.
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Respondents confidence level on online pre-payments

Risky Confident Opposed

Feelings about eco-packaging

Good Bad
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Mean Annual Income

Respondent Annual Income

Respondent 1 100,000

Respondent 2 90,000

Respondent 3 120,000

Respondent 4 110,000

Respondent 5 80,000

Respondent 6 150,000

Respondent 7 200,000

Respondent 8 96,000

Respondent 9 170,000

Respondent 10 70,000

Mean 118,600

Table of mean annual income

Respondents' annual income levels were within range making their perspectives of issues

more in line. Only one respondent had a total annual income of 200,000. Most of the respondents

were well placed around 100,000 per year.

Hypothesis tests were used to determine whether the hypothesis was confirmed by the

collected data. After analysis, it was established that the data collected was generally in line with

the set hypothesis hence validating the course of the research. Also, hypothesis testing was

pivotal in increasing the confidence level of the research process hence making the results more

generalizable. Confidence intervals of 95% were achieved meaning that the data was consistent
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with the established patterns in society. Future studies will most likely fall within the range of

the results of the research.

Explanation of the results for each inferential analysis technique to determine relationships

between or among variables (correlation or regression analysis). Describe how hypothesis

testing was used in this data collection and how it advances the accomplishment of the

research objectives.

A hypothesis was established regarding various research questions that were under

investigation. Data was collected to target the hypothesis and the research questions that

supported it. Once the data was collected; it was analyzed against the hypothesis. It was then

evident that the collected data was confirmed the hypothesis hence validating the premise of the

research. For instance, research indicates that most shoppers do not like paying for online

products before they can physically access the products to confirm their validity. This was a

premise that was confirmed by the hypothesis testing process when it was established that only

30% of respondents were confident with pre-payment.

Hypothesis testing provided reliability in the theory and the specific research questions

that were under investigation. Hypothesis testing enabled the research to establish the strength of

the evidence that was gathered from the sample. The data provided a basis through which the

researchers can make general claims describing patterns in the population. The findings in the

study were possible to extrapolate to represent the entire population that was under investigation.

For instance, feelings about eco-packaging in online shopping were very positive. At 90%

favorability, the researchers can conclude that online shoppers hold eco-packaging in high regard

and would much to ensure that such standards are kept. These patterns are consistent with

observations that are often made among populations. Most shoppers care about the sustainability
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of the processes by which they acquire their products. Many people prefer a process that is

sensitive to key global issues.