Examination week 6: Data Examination and Results
Data are mere facts and figures. Without data examination, no meaningful information
can be obtained from research. Data examination enables researchers to make informed
resolutions quickly, backing them up with facts provided by the data. Also, data examination
allows the uses of a research study to deeply understand the problem and potential solutions
hence building better businesses and relationships between the business and the customers.
I learned a lot about descriptive statistics, inferential statistics, and qualitative
examination of data. Descriptive statistics is the description or summarizing of data in a
meaningful way to establish relationships and patterns from the data (Byrne, 2007).
However, a researcher cannot make conclusions from descriptive statistics beyond the data
analysed. Also, a researcher cannot reach a conclusion concerning any hypothesis developed.
In other words, descriptive statistics simply provide a way to describe the data collected.
What I learned from descriptive statistics is that it is important in research as it helps in
visualizing what the data shows. Without it, it could have been very hard to visualize and
establish patterns on data collected. Also, I learnt that with descriptive statistics we can
present the collected data more meaningfully hence allowing a simpler way of interpreting it.
Inferential statistics allows a researcher to make inferences (predictions) from the
collected data. Inferential statistics involves taking samples from a populations and making
generalizations concerning the population (Byrne, 2007). There are two things that I learnt
about inferential statistics – estimating the parameters and testing the hypothesis. Estimation
of parameters refer to taking a statistic from the sample data and using this statistic to infer
something about the entire population. An example of sample data is the sample mean and an
example of a population parameter is the population mean. Testing the hypothesis involves
Data are mere facts and figures. Without data examination, no meaningful information
can be obtained from research. Data examination enables researchers to make informed
resolutions quickly, backing them up with facts provided by the data. Also, data examination
allows the uses of a research study to deeply understand the problem and potential solutions
hence building better businesses and relationships between the business and the customers.
I learned a lot about descriptive statistics, inferential statistics, and qualitative
examination of data. Descriptive statistics is the description or summarizing of data in a
meaningful way to establish relationships and patterns from the data (Byrne, 2007).
However, a researcher cannot make conclusions from descriptive statistics beyond the data
analysed. Also, a researcher cannot reach a conclusion concerning any hypothesis developed.
In other words, descriptive statistics simply provide a way to describe the data collected.
What I learned from descriptive statistics is that it is important in research as it helps in
visualizing what the data shows. Without it, it could have been very hard to visualize and
establish patterns on data collected. Also, I learnt that with descriptive statistics we can
present the collected data more meaningfully hence allowing a simpler way of interpreting it.
Inferential statistics allows a researcher to make inferences (predictions) from the
collected data. Inferential statistics involves taking samples from a populations and making
generalizations concerning the population (Byrne, 2007). There are two things that I learnt
about inferential statistics – estimating the parameters and testing the hypothesis. Estimation
of parameters refer to taking a statistic from the sample data and using this statistic to infer
something about the entire population. An example of sample data is the sample mean and an
example of a population parameter is the population mean. Testing the hypothesis involves
