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        <title>Blog  by Dr. Susan Carroll</title>
        <link>https://www.dissertation-statistics.com/dissertation-statistics-help-blog.html</link>

        <description>This dissertation statistics blog provides tips using the dissertation-statistics.com website. Subscribe here.</description>
        <language>en-us</language>
        <category>Dissertation Statistics</category>
        <pubDate>Tue, 27 Jan 2026 14:25:20 -0500</pubDate>
        <lastBuildDate>Tue, 27 Jan 2026 14:25:20 -0500</lastBuildDate>
        <copyright>dissertation-statistics.com</copyright>
    <item>
            <title>Apr 26, Research Designs: Avoiding the Headaches</title>
            <link>https://www.dissertation-statistics.com/dissertation-statistics-help-blog.html#Research-Designs-Avoiding-the-Headaches</link><guid isPermaLink="false">bada5d28fa97d99965d701eb194ac2b4</guid><description>Students that I work with are oftentimes despondent, frustrated and ready to quit altogether -  due to Chapter Three. The underlying culprit for this is the research design.  Unfortunately, many doctoral students have research designs that are poorly constructed. Some include innumerable variables - everything but the kitchen sink. Others want to change the world and have a design that would take years and years to complete. Others have no alignment among the design, the variables, the measurement tool, the research questions and the statistical analysis. Don't let these scenarios happen to you!  The purpose of the research design is simple. It is to guide the collection of data so that the results provided will be interpretable, defensible and generalizable. And hopefully it will be a satisfying experience for you so that you will have the confidence to do more research after the degree is completed.</description>
            
            <pubDate>Wed, 26 Apr 2017 16:00:54 -0400</pubDate>
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    <item>
            <title>Apr 26, Research Designs: Avoiding the Headaches</title>
            <link>https://www.dissertation-statistics.com/dissertation-statistics-help-blog.html#Research-Designs-Avoiding-the-Headaches</link><guid isPermaLink="false">bada5d28fa97d99965d701eb194ac2b4-cp</guid><description>Students that I work with are oftentimes despondent, frustrated and ready to quit altogether -  due to Chapter Three. The underlying culprit for this is the research design.  Unfortunately, many doctoral students have research designs that are poorly constructed. Some include innumerable variables - everything but the kitchen sink. Others want to change the world and have a design that would take years and years to complete. Others have no alignment among the design, the variables, the measurement tool, the research questions and the statistical analysis. Don't let these scenarios happen to you!  The purpose of the research design is simple. It is to guide the collection of data so that the results provided will be interpretable, defensible and generalizable. And hopefully it will be a satisfying experience for you so that you will have the confidence to do more research after the degree is completed.</description>
            
            <pubDate>Wed, 26 Apr 2017 16:00:49 -0400</pubDate>
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    <item>
            <title>Mar 20, Why We Need A Roadmap: Research Designs</title>
            <link>https://www.dissertation-statistics.com/dissertation-statistics-help-blog.html#Why-We-Need-A-Roadmap-Research-Designs</link><guid isPermaLink="false">2a71761b005dc3e1d7ab9dcb647ef0d8</guid><description>Research designs are your roadmap. They guide you in the collection of data so that your results will be interpretable and generalizable. 

Many things have to be considered in even the simplest of designs. The research questions, null and alternate hypotheses you are interested in; your key variables, how extraneous variance will be controlled;  how subjects will be selected, how large the sample should be, and assignment to groups or treatments if appropriate; how your data will be collected in a protocol that can be replicated in the future. 

Thinking all of this out in advance is required for a dissertation. It is a good process because if you don't know where you are going, any road can take you there. Give this design phase some time and strategic thought. You will be happy that you did.</description>
            
            <pubDate>Mon, 20 Mar 2017 00:00:00 -0400</pubDate>
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            <title>Mar 10, More Dissertation Sampling Strategies than just Random</title>
            <link>https://www.dissertation-statistics.com/dissertation-statistics-help-blog.html#More-Dissertation-Sampling-Strategies-than-just-Random</link><guid isPermaLink="false">9821ac8ba9091dd45dfd7471f34f0a4b</guid><description>Simple random sampling is the premier way to draw your sample.  There are other sampling strategies that are very useful as well.    Here is a summary of a few procedures that you can consider.





Systematic sampling is an often-used sampling strategy and cost effective.  Determine both the size of the population and the size of the sample you want to work with. Then, divide the sample size (n) into the population (N) size to get your key number, symbolized as “k”. You might use systematic sampling to select a sample of households in your community for a community survey.  The City Hall might have the listing already available, in random order and with ID numbers in sequence.  This saves you time and labor.  If the City Hall will give you a set of mailing labels, then it will be all the better.




Cluster sampling is exactly what its title implies.  You randomly select clusters or groups in a population instead of individuals.  This would work if a state wanted to sample all third graders on their writing skills.  They would randomly select third grade classrooms from all third grade classrooms in the state.  Each of those classrooms selected would have 100% of the students in that classroom in the sample.  The sampling unit or cluster is the third grade classroom not the individual student




Stratified sampling is used when the population is heterogeneous and it is important to represent the different strata or sub-populations.  There is a proportional representation of strata in the sample - proportional to the population strata. We divide the entire population into strata (groups) to obtain groups of people that are more or less equal in some respect.  Then, select a random sample from each stratum.  This insures that no group is missed and improves the precision of our estimates.   This might be used with different racial/ethnic groups if we wanted to insure that our sample included a proportional representation of African Americans, Asians and Latinos in addition to the Caucasians that pre-dominated our demographic pool.</description>
            
            <pubDate>Fri, 10 Mar 2017 13:57:38 -0500</pubDate>
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            <title>Mar  2, Population and Samples for Your Dissertation: The Difference!</title>
            <link>https://www.dissertation-statistics.com/dissertation-statistics-help-blog.html#Population-and-Samples-for-Your-Dissertation-The-Difference</link><guid isPermaLink="false">d5916f19972eda8a5fe5a962f569e8c5</guid><description>The population in statistics includes all members of a defined group that we are studying or collecting information on.The operative descriptor is “all” – all children under the age of 5, senior executives, first offenders, hospital patients, or the entire community of households in whatever geographic circle we are focused on. So the “population” in our statistical study is defined by the “who” (target group) and the “where” (the geographic boundary that this group exists in).





A part of the population is called a sample. Samples are studied to obtain valuable information about the larger group called the population. Once we define our population, we can take a sample of the population to conduct our statistics.A sample is a subset or subgroup of our population.It is a proportion of the population, a slice of it, a part of it and all its characteristics. 





A sample is a scientifically drawn group that actually possesses the same characteristics as the population – if it is drawn randomly.This may be hard for you to believe, but it is true.</description>
            
            <pubDate>Thu, 2 Mar 2017 12:09:41 -0500</pubDate>
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            <title>Feb 27, IRBs: Why Do We Have Them?</title>
            <link>https://www.dissertation-statistics.com/dissertation-statistics-help-blog.html#IRBs-Why-Do-We-Have-Them</link><guid isPermaLink="false">954d0ba1b15a6c18376f6244bca57ec3</guid><description>Did you ever wonder why you need to have IRB approval before you conduct your dissertation data collection? The U.S. Commission for the Protection of Human Subjects in Biomedical and Behavioral Sciences in the 1970's was created to protect human subjects in research studies. Their purpose was to ask: if risk to subjects was minimal; if the risks outweighed the benefits to society; if the selection of subjects was fair; if informed consent was sought and documented; if there was adequate provision to monitor data and spare injury;  and, to provide privacy and confidentiality. Those are the principles upon which IRBs were founded. And who can disagree with these?</description>
            
            <pubDate>Mon, 27 Feb 2017 09:52:49 -0500</pubDate>
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            <title>Feb 23, Getting Started on the Dissertation Topic</title>
            <link>https://www.dissertation-statistics.com/dissertation-statistics-help-blog.html#Getting-Started-on-the-Dissertation-Topic</link><guid isPermaLink="false">8e905cb213072e805e47f369435c3fd4</guid><description>One of the most difficult steps in the process of starting your dissertation is getting a topic.  Here are a few tips:





1. Find an appealing idea- something that excites you.





 You will be married to this topic for at least a year if not more! Get a topic that  makes a difference and is not a &quot; so what&quot; topic. This  should be something of interest to others-  as well as to you.





2.  Keep it the research design, sample and  data collection simple. 





You have to get a topic that will not take decades to investigate. So practicality of time as well as resources is a consideration. Also, you need to have a manageable dissertation topic.  The number of variables you incorporate can be alluring but overwhelming. Remember, you can always add variables later on when you have completed your dissertation and enter the real world of work or academia. Try not to become famous at this stage of the game. There is plenty of time for that once the doctorate is completed.  





3. Build upon what others have done and that you have discovered in the literature review.  





My own dissertation tested the trait-factor personality theory which says people gravitate to occupations based on their personalities. (Birds of a feather flock together.) This theory had been tested on lawyers, teachers and other occupations but I did it on allied health professionals. So I just replicated the study with a different population. Easy! And it was published in peer review journals and I presented it nationally. So you don't have to reinvent the wheel. 





GOOD LUCK</description>
            
            <pubDate>Thu, 23 Feb 2017 11:58:40 -0500</pubDate>
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            <title>Feb 20, How To Evaluate the Quality of a Journal Article</title>
            <link>https://www.dissertation-statistics.com/dissertation-statistics-help-blog.html#How-To-Evaluate-the-Quality-of-a-Journal-Article</link><guid isPermaLink="false">7282aa4bd41b8fddcc3674f66606ca8b</guid><description>A good research article to use for your Chapter Two should have the following elements: a concise abstract; an introduction that clearly states the purpose, the research questions and theoretical literature base upon which the study was initiated; the methodology  (subjects and sampling, instrumentation with validity and reliability, data collection procedures, data analysis for testing hypotheses); results of hypothesis testing and statistical significance;  discussion of results, practical implications, limitations and suggestions for future research. 

For the articles that meet the quality test and are aligned with your study topic, you should write abstracts of these elements. (I used index cards to do this because you can manually sort them in the correct fashion for Chapter Two writing.)  

An added benefit of this review is that each article has a REFERENCE section at the end. Here are other articles you may not have found that you can go to as well to complete your review of the literature. Also, journal articles have the names of authors and their contact information if you need to ask them a question or find out a little more about their instrumentation or methods.

This part of the dissertation may be the most difficult but it is a great way to become an expert in your area.  Spend the time to do this well.</description>
            
            <pubDate>Mon, 20 Feb 2017 00:00:00 -0500</pubDate>
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            <title>May  9, How to Get Respondents to Respond!</title>
            <link>https://www.dissertation-statistics.com/dissertation-statistics.xml</link><guid isPermaLink="false">b0d8a333d7869b7841fd820ece548b28</guid><description>Planning a party and then wondering if anyone will come is the same feeling researchers have when a survey is launched online or by mail. What if no one responds! We have found at Words &amp; Numbers Research that the quality of the questionnaire  stimulates a good return rate.  Here are a few tips that work. First, use different formats of questions and varied response scales on the questionnaire. This will be more interesting to the respondent than having 50 agreement scales for sentence-long items,  one after the other. Second, provide a specific set  of directions throughout about what you want the respondent to do. Confusion is a reason to toss the questionnaire or click off the site. Third, pay attention to the visual appearance of the questionnaire. It should be easy to read which means your choice of type face and use of color should be with that goal in mind. This is not an artistic exercise. Fourth, number all sections and number all items within a section.  It is easy for a respondent to skip a question accidentally, and missing data are costly to your analyses.  These pointers make a difference and are  easy to implement. It just takes a little time and care,  but the payoff is great.

NEW BOOK! How To Master Your Dissertation Data by Susan Rovezzi Carroll at Amazon, Barnes and Nobles and other online stores. Only $4.99 for the ebook!</description>
            
            <pubDate>Mon, 9 May 2016 12:52:05 -0400</pubDate>
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            <title>Apr 14, How to measure variables for statistics</title>
            <link>https://www.dissertation-statistics.com/dissertation-statistics.xml</link><guid isPermaLink="false">b0d8a333d7869b7841fd820ece548b28-cp</guid><description>Whatever variable exists, exists in some amount and can be measured. Measurement involves quantifying people, objects or events on their characteristics.  When we collect information about people, objects and events, we must turn that information into numbers so that we can measure it and make deductions about what we find out.  We must express it in numbers not just descriptive phrases. 

There are four scales for measurement: nominal, ordinal, interval and ratio. 

NEW BOOK! How To Master Your Dissertation Data by Susan Rovezzi Carroll at Amazon, Barnes and Nobles and other online stores. Only $4.99 for the ebook!</description>
            
            <pubDate>Thu, 14 Apr 2016 13:28:04 -0400</pubDate>
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