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Group A Reflection Summary Week 5Zach A Silva

RES/351

3.3.2014

Kristy PetersonGroup A Reflection SummaryDuring our discussions in week 4, we were able to cover our learning objective of defining and identifying open-ended questions along withdirect and indirect questions. We were able to identify when to use open ended questions, and those times in which it would be best to rely on closed questions to gain a better understanding form the testing subject. We also discussed and distinguished between research and investigation questions. Discussing the objective surrounding alternative response strategies were also helpful and provided a much needed bases to helping with seeing questions in a different light.

In week four we discussed how business research is conducted and learned different ways to improve statistical analytics in order to answer the questions for improving decision making. In order to create a solid business plan all these questions pertaining to the business are required. For example when opening a business you must consider your audience. Who will be benefitting from your service? Who will you target, males, females, the elderly, young folks, etc. Developing formulas and being able to interpret the data allows you to figure out how to gauge aspects of business using the appropriate methods for developing concrete statistics. Business research requires extreme amounts of planning.

During Week 5, we explored the different ways you can prepare data for analysis. We were introduced to data editing, data coding, and data entry. We learned data has three characteristics:

Central value

Is calculated by three measures of central tendency: mean, median, and mode.

Dispersion or variability of data

Is calculated by measures of variability: range, standard deviation, and variance.

Concept of central tendency and dispersion (along with computation of mean, median, mode, weighted mean, standard deviation, and so on)

Which are parts of descriptive statistics.

Chapter 16 discussed different types of graphs that can be used to express information and how to present business research findings. Qualitative and quantitative data often use bar graphs, pie charts, histograms, and stem plots, examples of these were provided in chapter 16.

We learned how to complete the business research process by determining which data analysis approach to use for the data set being utilized. Testing procedures consist of ANOVA, chi-square, single sample tests, and two-related tests to name a few. This week we were asked to differentiate among sampling methods (simple, random, systematic, stratified, cluster, convenience, judgment, quota, or snowball), levels of measurement (nominal, ordinal, interval, and ratio), and testing procedures.