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NR 439 Week 6 Discussion: Data Analysis and Results
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NR 439 Week 6 Discussion: Data Analysis and Results
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Week 6 Discussion: Data Analysis and ResultsData are mere facts and figures. Without data analysis, no meaningful information can
be obtained from research. Data analysis enables researchers to make informed decisions
quickly, backing them up with facts provided by the data. Also, data analysis 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 analysis
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
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