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Task#1(response to another student up to 6 lines sentence)What is Data Analysis? "Quantitative data analysis is defined as the process of utilizing a variety of statistical procedures to analyze numerical data" (Faulkner & Faulkner, 2014, pg.169). Data analysis is conducted in two steps: descriptive analysis and inferential statistics. "Data analysis involves counting responses and using other statistical procedures to discover the identifying characteristics of individual variables in a sample and the relationship between two or more variables in the sample" (Faulkner & Faulkner, 2014, pg 170). Descriptive statistics "are ways of organizing, describing, and presenting quantitative (numerical) data in a manner that is concise, manageable, and understandable" (Faulkner & Faulkner, 2014, pg. 170. A sample can be describe through measurable such as totals and percentages. Numerical descriptions can be used in both methods, it is not always used in qualitative methods, but must be used in quantitative methods. There is a table on page 171, that shows "Descriptive Statistics for Test Cheating". The cheating habits of 118 students. "Descriptive Analysis. Descriptive statistics helps us to make sense of a large amount of data by finding both what is common or typical for a variable and what exceptions exist for a variable" (Faulkner & Faulkner, 2014, pg. 172). Descriptive statistics allow us to aggregate data (to compile information in a concise, manageable, and understandable manner) so that data can be examined relatively quickly. We have probably used this technique most of our lives and not even realized it. "Univariate analysis involves the examination across cases of one variable at a time" (Faulkner & Faulkner, 201, pg. 172). Measures of Distribution. "Distribution of data is a summary of the frequency of individual values or ranges of values for a variable" (Faulkner & Faulkner, 2014, pg. 172). Frequency, as the word implies, is the number of times that a response occurs. There is a table that gives an example on pg. 173. Faulkner, S. & Faulkner, C. (2014). Research Methods for Social Workers. A Practice-Based Approach. 2nd Edition. Lyceum Books, Inc.
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View profile card for Krissy Grim Krissy GrimActions for reply by Krissy Grim
Mon at 12:50 PM
Hi Rhonda,
Good post. I thought it was interesting to examine the differences in qualitative and quantitative studies. As you mentioned, quantitative research utilizes numerical data by analyzing it. Qualitative research is exploratory. It can also utilize descriptive methods, these types of methods are used when little is understood about the topic (Faulkner & Faulkner, 2014).
Task#2(same as above)
Measure of Dispersion
A measure of dispersion takes a look at the variation of data and their differences. Measure of dispersion also records the arrangement of scores surrounding the mean. “Measures of dispersion are used only for studies with interval- or ratio-level data” (Faulkner & Faulkner, 2014, p. 175). Range is also a simple example of a measure of dispersion. Range focuses on the difference between the lowest and highest variable. “Variance is a statistical measure used to examine the spread of scores in a distribution. The larger the variance, the farther the scores are from the mean; the smaller the variance, the closer the scores are to the mean” (Faulkner & Faulkner, 2014, p. 175).
Histograms are utilized to show intervals and ratio-level information. This information discloses the scores which surround the mean or known as leptokurtosis distribution. “Leptokurtosis is the shape of a distribution of scores that is tall and narrow because the majority of scores closely resemble the mean” (Faulkner & Faulkner, 2014, p. 175). In figure 11.2 a histogram is shown. This type of histogram coveys that there are differences in the scores from the mean. Platykurtosis is this type of distribution shape (Faulkner & Faulkner, 2014).
The last type of distribution is one you may have more commonly heard of standard deviation. “A standard deviation is a measure of dispersion that is calculated by taking the square root of variance (Faulkner & Faulkner, 2014, p. 176). Standard deviation is frequently used. There are two thoughts made when glancing at a standard deviation. The first assesses whether the deviation focuses on interval-level or ratio-level variables. The second assessment is seeing whether the information is normally distributed. “Normal distribution of data is the symmetrical distribution of scores around the mean, with the most scores clustered around the mean and tapering off on both sides” (Faulkner & Faulkner, 2014, p. 177). When the mean is zero and the shape of the graph looks like a bell this is indicative of normal distribution (Faulkner & Faulkner, 2014).
My thoughts
Oh my, I must say it took a lot to understand these sections. I am familiar with deviations, however, I think if I worked frequently with them it may seem a little clearer. I felt like this was math class! Even though charts are supposed to help you better understand data you must be able to interpret them correctly. I do think this section began to touch on how to understand different kinds of distributions and deviations. Good luck everyone on the upcoming quiz.
Reference
Faulkner, S. S., & Faulkner, C. A. (2014). Research Methods for Social Workers A Practice-Based Approach (Second). Chicago, Illinois: Lyceum Books, Inc.
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View profile card for Rhonda Reynolds Rhonda ReynoldsActions for reply by Rhonda Reynolds
yesterday at 7:01 PM
Hi Krissy, good post. I know what you mean about math class. I am so glad to be done with Algebra. lol. Looking at graphs sometimes help to figure out things, other times I get confused and have to really study to try to figure things out. Good luck to you on the quiz.
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View profile card for Holly Withrow Holly WithrowActions for reply by Holly Withrow
yesterday at 7:50 PM
I think you did a very good job of describing the measures of dispersion. And you are correct that there is some math involved, more complicated than figuring measures of central tendency (mean, media, and mode). I took statistics and this reminded me of a lot of terms and concepts I had forgotten. The bell curve, asymmetrical curves which are skewed left or right, and the types you mentioned above (leptokurtosis and platykurtosis). All good stuff. I also agree that being able to understand the charts can be challenging. I am definitely experiencing this in my Intro to Environment Science class where I'm looking at charts that meteorologists created and they are way above my head (i.e oceanic temperatures surrounding the El Nino phenomenon). Sometimes I really have to study them for a long time or google the terms to understand how to interpret them. Great work, again. And good luck to you as well!

Task#1(response to another student up to 6 lines sentence)What is Data Analysis? "Quantitative data analysis is defined as the process of utilizing a variety of statistical procedures to analyze numerical data" (Faulkner & Faulkner, 2014, pg.169). Data analysis is conducted in two steps: descriptive analysis and inferential statistics.

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