Discussion: Descriptive Statistics Study Guide

Discussion: Descriptive Statistics Study Guide

Discussion: Descriptive Statistics Study Guide

Group A, Chapter 16: Descriptive Statistics Study Guide

Odecir Gocking, Brittney Hornbuckle, Samantha Pitt, Emily Reiter, Anna Woody, and Elena Boersma

Descriptive Statistics

Allows researchers to describe and summarize quantitative data and helps with understanding

research evidence (Polit & Beck, 2017).

Four Levels of Measurement

Nominal Measurement: used to assign variables/characteristics/categories as a number or as a symbol to represent a category (Polit & Beck, 2017). The numbers used in nominal measurement are not used as a quantifiable meaning but rather used to identify the variable i.e. to code the genders of a sample 1 = male, 2 = female (Polit & Beck, 2017).

Ordinal Measurement: a measurement that shows where/how an object or people are sorted and where they rank on an attribute level or how they are coded into a group i.e. a person who is independent could be coded (1), one person assist (2), two-person assist (3), mechanical lift (4) (Polit & Beck, 2017). Ordinal measurement tells us the ranking of the level of the attribute (Polit & Beck, 2017).

Interval Measurement: refers to the distance between the rank of an attribute i.e. a temperature of 80 degrees Fahrenheit is 20 degrees warmer than 60 degrees Fahrenheit (Polit & Beck, 2017).

Ratio Measurement: have an absolute zero, therefore mathematical equations are allowable (Polit & Beck, 2017). This is the highest level of measurement and is known as the interval or ratio scale (continuous) (Polit & Beck, 2017).

Critiquing Descriptive Statistics

Descriptive statistics are an important part of biometric analysis for the understanding of further

statistical evaluations.

· Medical data is based on a collection of the data of individual cases or

objects

· The goal of a scientific study must always be clearly defined

· If the data are of good quality conclusions can be drawn

· The definition of the value determines the level of measurement of the variable

Frequency Distributions

Used to systematically organize numeric data from lowest to highest and allows the researcher to visualize the data system (Polit & Beck, 2017). Histograms (bar graphs) and Frequency Polygons (dot line graphs)- Graphs used to display interval and ratio level data,

Shapes of Distribution

1) Symmetric- graph can be folded in half and mirror each side-data is mirrored.

2) Skewed- the peak of the graph is off center-asymmetric; one tail is longer than the other. a. Positive skew- the tail of the graph is to the right b. Negative skew- the tail of the graph is to the left

3) Modality- graph displays the number of peaks within the displayed data

a. Unimodal- one data peak b. Multimodal- two of more data peaks

c. Bimodal- two data peaks

d. Normal- the data displayed is symmetric peak within the graph.

Central Tendency Frequency- distribution in the center of a distribution or the average. The results of the three indexes below will provide results in skewed distributions as previously defined (Polit & Beck, 2017).

Modes- Most frequent occurring value in a distribution i.e. median (the data middle point) and the mean (the data added together).

Risk Indexes- The risk index is the result of a risk assessment. Indexes can be used in the calculation of:

· The likelihood index shows the probability of a risk event occurring

· It is a composite of the likelihood and impact index

· Risk assessment can be used to calculate this index

· Impact index shows the impact a risk event has

Variability – The term that represents the spread or distribution of data from narrow to wide or somewhere in between (Polit & Beck, 2017).

Range – represents the highest score or distribution “minus the lowest score in a distribution (Polit & Beck, 2017, p. 362). Range is often not an accurate representation of data and is often only used to show an overall description of the data (Polit & Beck, 2017).

Standard Deviation (SD) – informs the researcher how much measurements are spread out from the average (mean) of the data. SD can be narrow-meaning the spread of numbers is close to the average in either direction or it can be wide-meaning the spread of numbers is at a distance from the average in either direction (Khan Academy, 2019). Additionally, SD can also be calculated to find individual data scores (Polit & Beck, 2019).

Variance – is the SD before the square root is calculated and it is used in used statistical testing (Polit & Beck, 2017).

Bivariate Descriptive Statistics

Bivariate Descriptive Statistics describes the relationship between variables by the methods of crosstabs tables and correlation indexes. (Polit & Beck, 2017).

Crosstabs Tables

Crosstabs tables are where the frequency of two variables are cross tabulated i.e., when deciphering whether it is males or females who are heavy, light or nonsmokers, the numerical data for all women nonsmokers is placed in the table, and then the data for all male nonsmokers (Polit & Beck, 2017). The numerical data for all light and heavy smokers for each gender is also placed in the table and each numerical data is presented as a percentage (Polit & Beck, 2017). From the total of the percentage one can conclude whether it is males or females who are indeed the heavier smokers (Polit & Beck, 2017). This data can be further broken down to compare each category whether women were more likely than men to be nonsmokers and less likely than men to be heavy smokers (Polit & Beck, 2017). The table will provide the opportunity for one to conclude which gender is in fact the heavier smoker by evaluating the percentage (Polit & Beck, 2017).

Correlation

Relationships between two variables are described through correlation procedures with the question usually being to what extent are two variables related to each other (Polit & Beck, 2017).? For example, to what degree are anxiety scores and blood pressure readings related? The correlation between two variables can be graphed as a scatter plot which is a coordinate graph (Polit & Beck, 2017). The two variables are laid out at right angles: one variable is labeled “X” and is scaled on the horizontal axis and the other variable is labeled “Y” and is scaled vertically (Polit & Beck, 2017). So, the first variable would be located on the graph, then the location would be where the “X” and the “Y” variable meets. If the slope on the graph begins on the lower left corner and rises to the right then the relationship is said to be positive (Polit & Beck, 2017). A positive correlation occurs when high values on one variable is associated with high values on another variable while a negative relationship is one which high values on one variable are related to low values on the other (Polit & Beck, 2017).

When relationships are perfect it is possible to predict the value of one variable by knowing the value of the second (Polit & Beck, 2017). For example, if all people who are 5 ft 9 inches tall and are two hundred pounds, we can then automatically know the height of everyone who is two hundred pounds. When the relationship is not perfect one can assume the degree of correlation by seeing how close the points on the graph cluster around a straight line. If they cluster close to each other the correlation is strong and if the points are scattered over the graph then the relationship is nonexistent (Polit & Beck, 2017).

The most widely used correlation statistics is the Product-moment correlational coefficient which is also called Pearson’s r (Polit & Beck, 2017). This coefficient is computed with variables measured on an interval or ratio scale (Polit & Beck, 2017). Spearman’s rho is a correlational index for ordinal level data (Polit & Beck, 2017).

Conclusion

Clinicians are required to keep up on current information that could potentially help and provide patients with quality care. As mentioned by Harvey (2018) descriptive statistics are used to summarize sample characteristics, describe key variables, and document methodical formulas. Descriptive statistics helps to understand quantitative research evidence, communicate the sample study, and communicate the values of key outcome variables.

References

Harvey, E. (2018). Statistics for Nursing: A Practical Approach. Jones & Bartlett Learning. Retrieved from:

https://books.google.com/books?hl=en&lr=&id=bpdNDwAAQBAJ&oi=fnd&pg=PP1&dq=descriptive+statistics+in+nursing&ots=lvYPVg68zd&sig=ow9G2Wpy4S4R1yfVRylJ1E4eOZc#v=onepage&q=descriptive%20statistics%20in%20nursing&f=false

Khan Academy. (2019). Calculating Standard Deviation Step by Step. Retrieved from https://www.khanacademy.org/math/probability/data-distributions-a1/summarizing-spread-distributions/a/calculating-standard-deviation-step-by-step

Polit, D. F., & Beck, C. T. (2017). Nursing Research Generating and Assessing Evidence for Nursing Practice. Philadelphia: Wolters Kluwer.

Discussion: Descriptive Statistics Study Guide

Discussion: Descriptive Statistics Study Guide

You must proofread your paper. But do not strictly rely on your computer’s spell-checker and grammar-checker; failure to do so indicates a lack of effort on your part and you can expect your grade to suffer accordingly. Papers with numerous misspelled words and grammatical mistakes will be penalized. Read over your paper – in silence and then aloud – before handing it in and make corrections as necessary. Often it is advantageous to have a friend proofread your paper for obvious errors. Handwritten corrections are preferable to uncorrected mistakes.

Use a standard 10 to 12 point (10 to 12 characters per inch) typeface. Smaller or compressed type and papers with small margins or single-spacing are hard to read. It is better to let your essay run over the recommended number of pages than to try to compress it into fewer pages.

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The paper must be neatly formatted, double-spaced with a one-inch margin on the top, bottom, and sides of each page. When submitting hard copy, be sure to use white paper and print out using dark ink. If it is hard to read your essay, it will also be hard to follow your argument.

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Discussion Questions (DQ)

Initial responses to the DQ should address all components of the questions asked, include a minimum of one scholarly source, and be at least 250 words.
Successful responses are substantive (i.e., add something new to the discussion, engage others in the discussion, well-developed idea) and include at least one scholarly source.
One or two sentence responses, simple statements of agreement or “good post,” and responses that are off-topic will not count as substantive. Substantive responses should be at least 150 words.
I encourage you to incorporate the readings from the week (as applicable) into your responses.
Weekly Participation

Your initial responses to the mandatory DQ do not count toward participation and are graded separately.
In addition to the DQ responses, you must post at least one reply to peers (or me) on three separate days, for a total of three replies.
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Part of your weekly participation includes viewing the weekly announcement and attesting to watching it in the comments. These announcements are made to ensure you understand everything that is due during the week.
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Familiarize yourself with APA format and practice using it correctly. It is used for most writing assignments for your degree. Visit the Writing Center in the Student Success Center, under the Resources tab in LoudCloud for APA paper templates, citation examples, tips, etc. Points will be deducted for poor use of APA format or absence of APA format (if required).
Cite all sources of information! When in doubt, cite the source. Paraphrasing also requires a citation.
I highly recommend using the APA Publication Manual, 6th edition.
Use of Direct Quotes

I discourage overutilization of direct quotes in DQs and assignments at the Masters’ level and deduct points accordingly.
As Masters’ level students, it is important that you be able to critically analyze and interpret information from journal articles and other resources. Simply restating someone else’s words does not demonstrate an understanding of the content or critical analysis of the content.
It is best to paraphrase content and cite your source.
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Review your similarities. Did you forget to cite something? Did you not paraphrase well enough? Is your paper made up of someone else’s thoughts more than your own?
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The university’s policy on late assignments is 10% penalty PER DAY LATE. This also applies to late DQ replies.
Please communicate with me if you anticipate having to submit an assignment late. I am happy to be flexible, with advance notice. We may be able to work out an extension based on extenuating circumstances.
If you do not communicate with me before submitting an assignment late, the GCU late policy will be in effect.
I do not accept assignments that are two or more weeks late unless we have worked out an extension.
As per policy, no assignments are accepted after the last day of class. Any assignment submitted after midnight on the last day of class will not be accepted for grading.
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Communication is so very important. There are multiple ways to communicate with me:
Questions to Instructor Forum: This is a great place to ask course content or assignment questions. If you have a question, there is a good chance one of your peers does as well. This is a public forum for the class.
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