Hi Everyone
Hang in there. We are just about done. Here are the lecture notes. We need to focus on our hypotheses. Continue to look at your hypotheses and cast them into forms like those we discussed in class.
Tarynn
Hi All
Well, the finish line is clearly in sight. We went over a good deal of stuff. We reviewed the paper format in more detail and discussed all of the different ways to enter data and to begin to set up our database. You should be focusing on data entry and thinking about data analysis. At this point, you should be ready to begin the actual analysis of your data.
Please bring your SPSS database to class next week, even if you have not yet finished entering all of your cases. Also bring at least one hypothesis to class with you. You will need this to do this lecture. We will be focusing on setting up hypothesis testing and looking at how to do it both manually and via SPSS. You should now have read all the way through the end of the book. This means that you have read the chi-squared chapter as well. If you haven't, please do that too. No notes this week.
See you all next week.
Tarynn
Hi Everyone
Well, we are down to the home stretch. And I know that you are all feeling the pressure. Continue to stay focused on the goal and you will do fine. Please remember to continue to work on your research papers and presentations so that all you have remaining is to fill in your data analysis, resullts and conclusions.
This week we covered the beginning of hypothesis testing. We began by introducing the t-distribution. We discussed why we need to use the t-distribution and how to use the t-tables. We introduced the concept of degrees of freedom "df = n-1" (don't forget to subtract the 1) and the idea of one and two-tail tests and how that affects the way we read the t-table. We discussed different conditions on sample sizes and when one would use t-tables vs. z-tables.
Next we introduced the idea of hypothesis testing and looked at some examples of how it would be used to test some of the hypotheses that we were working on in our class projects. We looked at how the idea of the confidence interval could be used in our hypothesis testing and showed how hypothesis testing was simply looking at whether or not our null hypothesis assumption fell inside or outside of our confidence interval.
Please make sure to read the SPSS manual chapters and re-read the chapter in the book. We will do more examples next time and we will conclude with looking at chi-squared testing.
Tarynn
This week's notes Download file
Last week's notes Download file
Hi Everyone:
Well, that was a hard class but I think we made it through the estimation chapter and now we begin that last of the course. You are on the home stretch now everyone. So stay focused on your work.
(1) Keep developing your presentation materials
(2) Make sure you have been working on your paper. Even if you don't have data. Get the introduction done and the bibliography done. Get the cover page typed and a page set up for the abstract.
Keep me posted on any IRB issues or any data gathering issues. Attached are the notes from this week's lecture. Go over them. Make sure you know how to do the confidence values for difference confidence levels and how to find the appropriate z-value. If you have trouble, see me.
Tarynn
Hi Everyone
Well, that certainly was an attack of sillies yesterday wasn't it?! But, I guess we needed it. It was pretty confusing for a first go-over. So let's review everything:
(1) We reviewed the basics of sampling and discussed the notational differences between the sample parameters and the world or total population parameters
(2) We discussed different kinds of sampling and the problems associated with the different sampling protocols.
(3) We discussed some basic probabiliy and how to define the probability P(E) that an event E would occur.
(4) We discussed how to use SPSS to draw a random sample from a dataset
We then went and examined the problem of estimation of population parameter values from samples of that population. We noted that there are two kinds of estimates, point estimates and confidence interval estimates.
(5) We looked at what a confidence interval meant and how one would define a confidence interval using the area under the normal curve
(6) We then used this argument and used the z-table to understand how to computer the z-score associated with a certain "degree of confidence" for a result. That is, "I would like to be 95% sure that my confidence interval contains the true population mean." We translated this into a graph that we then used to find the associated z-score for different degrees of confidence. We called this the z-score of confidence or zconf.
(7) Using the idea of area under the curve, we then demonstrated how we could use the z-transform equation to calculate the confidence interval formula for the population mean, based upon knowing the sample mean and the sample standard deviation. At this point, we all got very giddy and decided to go home because our brains were fried. So here are the lecture notes for today.
Lecture 12 Sampling/Estimation Lecture Notes
Have a great week everyone. We will continue this work and move into the next chapter.
Tarynn
Continue reading "Lecture 12 - Semester 2 - Take Home Message" »
Hi All
Hopefully you have all had a great rest from your vacation. Today in class we reviewed z-scores and how to use them to find probabilities of different events occurring. We also talked about sampling and problems with sampling design. In particular, we addressed random sampling, stratified sampling and related issues. We also talked about how to use SPSS to draw a random sample from a data sample. For next week you are to (a) begin studying for your exam, (b) continue your project data work, (c) re-read the chapter on sampling and read over the chapter on estimation. I am attaching the lecture notes for today's class. Lecture Notes
See you all next week
Tarynn
Hi All-
Greetings from overseas in Athens, Greece. The weather here is moderate, in the low to mid 50's. But it is raining and that makes climbing through archeological dig sites a bit of a mess. Today you should be listening to Dr. Ayn Welleford discuss qualitative methods, with a particular focus on grounded theory. In case you did not receive the uploaded file for her lecture notes, here it is again - Qualitative Lecture Notes - Dr. Ayn Wellford
See you all in one week.
Tarynn
Hi All-
In this lecture we went over the material on z-scores and distributions. We looked at how to use SPSS to create Z-scores. We used z-scores to help us interpret different kinds of probabilities of events happening in a distribution. We were reminded that next week Dr. Ayn Welleford would guest lecture and then we had vacation.
See you all in two weeks.
Tarynn
Hi Everyone
Well, this was our comprehensive review of Chapter 8 of the text book. We re-reviewed all of the material and did a number of problems to make sure that everyone new how to do the following:
(1) Plotting all of the different 2 and 3D plots we have discussed including interactive 3D.
(2) Using the Transform -> Compute mode of SPSS to compute actual values, residual values, error and sum square error
(3) Running the Linear Regression and Interpreting Results .
At this point we are now done with this material and are moving on to the next chapters. You are to read Chapter 9 in your text book as a review. We will not be covering it.
Tarynn
Hi All
Surprise, surprise! 1 more lecture and we are half way through the course. Let's review today's lecture.
(1) We reviewed concepts of association and causality .
(2) We talked about what a PRE measure was about.
(3) We reviewed SPSS cross-tabs and how to get the different association measures in SPSS.
(4) We defined the general concept of a PRE measure and informed vs. uninformed guessing.
(5) We defined the PRE measure lambda and discussed how to calculate it and interpret it. We also defined E1 and E2 errors used in the calculation of lambda and how to calculate them. We observed that lambda is good when you have nominal data.
(6) We defined the PRE measure gamma and discussed how to calculate and interpret it. We observed that it required us to understand the concept of concordant pairs and discordant pairs and how to calculate them. We observed that gamma is good when you have ordinal data.
(7) We used SPSS to introduce the concept of a scatter graph to begin to understand relationships.
Next week please read the chapter on regression. Continue to frame your hypotheses in terms of contingency tables and the questions you intend to ask.
Have a good one
Tarynn
Hi All
Hope you are having a good Turkey Day and are continuing to review the material you have not had a chance to really digest (along with the turkey). Remember to be formulating questions, based upon your hypotheses, that can be tabled like contingency tables. See you all in a week.
Tarynn
Hi Everyone-
Wow! What a day that was. We covered a whole bunch of new concepts but we really didn't do much math. Whew! So let's see what we are supposed to have taken home from this week's lecture.
(1) We reviewed construction of a contingency/cross-tab table and what all of the different parts of the table mean. We also covered how to interpret the different components.
(2) We discussed independent/dependent variables and how to read the question a table was asking.
(3) We covered how to compute row, column, and total percent and how to interpret what the different cells and combination of cells mean under the different percentage calculations.
(4) We saw a way to illustrate a contingency table graphically using mosaic displays .
(5) We covered the concepts of odds, conditional odds, and odds ratio , what each means and how to interpret each of them.
(6) We reviewed how to make SPSS do contingency table/cross tab analysis. And we discussed how to interpret the output results.
(7) We then looked at how to determine the existence of an association between variables and we introduced idea of a the bubble plot as an easy way to begin to interpret contingency tables and to look for associations.
(8) We followed this with a discussion on different contingency tables and bubble plots and what they would look like for different types of association. We illustrated positive and negative association and how we could use the odds ratio to help us see if an association exists. And we finished this by discussion the idea of strength of a relation and what type of scale is usually used. We also talked about linear and nonlinear associations.
(9) We closed our discussion with the concept of causality . We discussed what causality meant and what some of the requirements were to have a causal association, and we introduced the idea of a spurious relationship. We also illustrated how to use SPSS layers in Cross-Tab to help determine if a spurious relationship exists.
Don't forget to reread your chapters during the week that I will not be here. When I return, we will be working hard to finish the material on measures of association and move on to linear regression. Read in the textbook about the association measures lambda and gamma because we will be covering them in detail. Those of you that did not hand in your Step 2 paper, make sure you have it ready for the next class.
Please begin to think about how contingency tables might apply to your research effort. Think about your measurement instruments and other information that you will be recording and how you might formulate questions in terms of contingency tables as they relate to your hypotheses. Also, begin to seriously consider the question of how you will create your SPSS database.
Have a great next two weeks
Tarynn
Hi Everyone-
Do you realize that we are now 2/3 of the way through the first semester and 1/3 of the way through the academic year! And wow! What an intense and dense lecture that was. Lots of material to learn. And we sure covered a wide variety of new equations and concepts. So let me see if I can summarize what you should have taken home from this lecture.
In this class we covered the detailed concept of dispersion or spread of a distribution.
(1) We reviewed the range and discussed why it is a very rough descriptor of the dispersion of a distribution.
(2) We introduced the concept of the IQV - Index of Qualitative Variation as an alternative descriptor of variation that is particularly useful when one wishes to compare between groups whose categories are nominal descriptors.
(3) We next introduced the concept of variance and standard deviation . We discussed the idea of deviation from the mean value and how summing the squares of the deviations of each value from the mean would be a useful measure of the total variation of the distribution. This gave us the concept of the sum squared deviation or SS . We then used this to demonstrate how to compute the variance and standard deviations. We talked about how there were different notations for when one is computing the variance of the total population versus a sample of the population. And we also covered some alternative formulae for computing the mean and variance because there are problems using the definitional equations.
(4) We then discussed the meaning of the variance/standard deviation in terms of area under the "bell curve" and how that is useful. We examined, using the bell curve, what happens when the standard deviation is small versus when it is large.
(5) We then looked at how to compute the standard deviation and the variance from grouped data . We observed that the formula for doing this is methodologically similar to the way we computed the mean for grouped data.
(6) Next we introduced the concept of the IQR - Interquartile Range . We defined it and discussed why it is a more stable range value than the actual range. First we considered how to compute the IQR using the exact data. We then considered how to construct the IQR by revisiting the formula for constructing the median quartile using grouped data. We did some examples where we computed Q25 and Q75 using the grouped data and we demonstrated how the formula for Q50 (median) could easily be altered to compute the "tile" data for any desired "tile".
(7) We next covered boxplots and modified boxplots . We discussed how they are constructed and how to interpret them.
(8) We addressed the question of how one ethically decides when a data point or points can be considered to be an outlier. To do this, we defined the constructs of upper fence and lower fence . We then stated the rule that a datapoint that falls outside the fence may be considered to be an outlier once you have checked to make sure that you have entered the data correctly from the data sheets and that there is no problem with the data in the database.
(9) We then discussed the problem of scales. We observed that some data can be on a different scale of magnitude than another. We observed this when we did clustered bar graphs and histograms and discovered that the frequency scales were quite different in our example. We talked about how one can "lie" with graphs and how to avoid this problem by scaling to percentages. We also introduced the concept of CV - Coefficient of Variation as a way of scaling the variation so that distributions that are at different scales can be compared.
(10) We closed our discussion with a Halloween scare from Tarynn who showed us the actual equations for calculating skewness and kurtosis . But we were reassured that we would not actually have to use them. We discussed how to interpret the skewness and kurtosis measures and what the standard error of skewness and kurtosis meant.
(11) In SPSS we went over some new features of the bar graph and we discussed how to create a boxplot . We also addressed how to enter data into an SPSS spreadsheet in a way that makes it more amenable for plotting boxplots. We also went over the remainder of the measures of dispersion in the Analysis component of the SPSS modules we have previously covered.
Don't forget to do your practice problems. Have a great week.
Tarynn
Hi Everyone
Well, you should all have at least one problem done on the examination by now. And many of you have noticed that question two duplicates question 1. So, do not do question 2. Remember, do not let the test wait for the weekend. Do one question per day. Save Sunday to go over the whole test and make sure you have everything completed and checked. Remember, CITI examination certificates are due this week as well. And, re-read chapter five of the text book. I will be available for questions whenever you need. Feel free to call, email, stop over at the office, make an appointment, whatever.
Take care
Tarynn
Hi Everyone -
We will be meeting in the SMART board Room 104 of the Trani Center again this coming week. Now, let's catch up on what we have now covered in Chapters 1-5 of the textbook. In our last lecture we reviewed a number of concepts and introduced a few more. So let's summarize:
(1) We reviewed the idea of a distribution and we introduced the relationship between the count/frequency distribution, the probability/fraction distribution, and the percentile distribution. We also reviewed the cumulative frequency/percent/probability distribution and what it meant.
(2) We reviewed the major properties of a distribution (a) Central Tendency or Clustering, (b) Dispersion or Spread, (c) Skewness or Tailness, (d) Symmetry.
(3) We reviewed summation notation and did a few new types of problem to make sure everyone new how to use the summation notation.
(4) We reviewed measures of clustering/central tendency and how to compute them for frequency data when the data is not grouped: (a) Mean, (b) Median, and (c) Mode.
(5) We reviewed the properties of max, min, and range as well.
(6) We then reviewed all of the previously covered SPSS functions under File, Edit, Graphs, and Analysis. We also reviewed how to import an Excel spreadsheet into SPSS and how to add the Labels to the variable columns.
(7) We covered how to export a graph/chart as a JPEG image file to a MS Word document. We also covered how to make changes in the document once it was pasted into the document. We covered how to align it (left, center, right) and we covered how to resize it.
You should all have been working on the Worksheet 1 problems and be bringing them to class with you. In preparing for the first test, you should know that I will feel very comfortable in asking you to do any of the SPSS, Excel, and MS Word items above. You should also be reviewing all of the Chapter 1-5 material for the examination. Please make sure to ask any questions you might have in the class.
(8) We discussed the status of the IRB Step 1 documents. All individuals should now be reviewing the comments on those documents and making sure that they understand them.
If you have any questions on your IRB Step 1 paper, please make sure to either see me before/after class or make an appointment to go over the material with me right away.
(9) CITI Exam Certififications are due 24 October 2005. Please make sure you complete this asap. I am still missing some CITI certificates.
(10) Everyone should now be reviewing the guidelines for the IRB Step 2 paper. You should be looking over the IRB sample packet handout and beginning to construct your answers to all of the items in the packet. You should also have downloaded blank forms for yourself so that you can begin to fill them out.
Have a great week
Tarynn
Hi Everyone-
Well, we all had a new experience as we began using real mathematics. Hopefully people didn't get too scared about it as we began to see how it is just a foreign language like any other language. Remember, we will be meeting next week in the Trani Life Sciences Building Room 104 classroom again. So please come directly there. WARNING: You have until this Friday at 5pm to hand in your Step 1 paper, if you have not done so.
Let's summarize what we need to take home from today's class.
(1) We went over the idea of a distribution and its properties. We talked about "count" or "frequency" distributions. We discussed how a distribution might arise and why it would be of interest to us. And we mentioned the idea of percentile and probability distributions and why we would wish to use one of them rather than a frequency/count distribution. [Chapter 2]
(2) We talked about three major properties of distributions: (a) Central Tendency or Clustering, (b) Dispersion, and (c) Skewness and we illustrated what these properties meant. [Chapter 4]
(3) We went over "summation notation" and how it works. We realized that summation notation is just a short hand way to tell us to do a particular set of mathematical operations. And we were reassured that this was about as hard as the mathematics was going to get. [Chapter 4]
(4) We talked about measures of clustering/central tendency and then defined the following properties of a variable/distribution: (a) Median and (b) Mean. We also defined the Mode and the Range of a distribution. [Chapter 4]
(5) Using SPSS, we illustrated how sampling variation can make a difference in how we interpret our results and discussed how this might impact the way we go about deciding how to do our sampling for our research projects. [Chapter 1]
(6) We illustrated how to use some of the basics of SPSS. In particular, we examined how to use some of the elements in the File, Edit, Graphics and Analysis elements.
(7) In the File element, we examined: (a) New and the sub-option data, (b) Open and the sub-option data, (c) Save and Save As, (d) Recently Used Data and Files.
(8) In the Edit element, we examined Copy and Paste.
(9) In the Graphs element, we reviewed a number of items: (a) Gallery - which provides information on all of the different options available for graphing data and provides help as well, (b) we used the Bar Graph, Line Graph, Pie Chart and Histogram to illustrate our data. We talked about why one would use one choice over the other and some of the "lies" of illustrating data incorrectly. [Chapters 2, 3]
(10) In the Analysis element, we reviewed how to use the Descriptive Statistics component. And, we examined the frequencies and descriptives sub-options within that component. [Chapters 2, 4]
With this lecture, Chapters 1-4 of the textbook should be beginning to coalesce into a more sensible state for you. We are currently off by one lecture. So please re-read the material in Chapters 1-4 of the book. If you wish to get ahead, read Chapter 5. We will be focusing, next time, on the remainder of Chapter 4 and the beginning of Chapter 5.
Have a great week
Tarynn
Hi Everyone -
Well, here we are, already through Lecture 5 (one third of the way through the first semester of your 2nd year). Who would have thought it! So, let's summarize what we have completed to this point.
(1) We have gone over the basics of how to do a literature search. We have covered VCU literature searching, literature searching on the web through Highwire and PubMed, general and specific internet search engines and internet metasearch engines of different kinds. You should now have a solid grip on how to use these basic methods and be able to use such search engines as Highwire, PubMed, Ovid, InfoTrak, Silver Platter, WebSpirs and such internet engines as Dogpile, Clusty, Kartoo and Exalead.
(2) We have gone over the essence of what research is all about and the basic stages of research. You should be able to summarize the steps involved in research and what the important factors are associated with each of those steps.
(3) We have briefly covered the history of ethical issues in research and talked about some of the ethical problems arising in research. You have been answering weekly dilemmas addressing some of those issues and you have been pursuing the completion of your CITI examination or have already completed it by now.
(4) We have focused on the formulation of a general research question, narrowing the research question, creation of the null hypothesis (the hypothesis of no change/difference) and the alternate hypothesis (the hypothesis of difference or change) and we have focused on how to correctly state these so that they are scientifically sound.
(5) We have been introduced to the basics of SPSS. In particular, we now know how to open SPSS and examine the data and the variable pages. On the variable page, we know what the various columns mean and the very barest of basics of how to enter the variable information for each of those columns.
So, as you can see, you have learned quite a bit in a short time. Remember, I am here if you need help. Don't forget, your Step 1 - Preparing the IRB Proposal paper is due this coming week.
Have a great week
Tarynn
Hi All -
Today's take home messages are:
(1) Metaphors of reality. How we see the world is brought to the table when we formulate our research question, our hypotheses, and the way we carry out our research. It is critical to be aware of self when doing research.
(2) Nothing about us, without us. When carrying out research, thinking about your question as it relates to the group under study is important. Is the question important to you? Is it important to the group? How important is group input to your study, before you start? Do you need to do a focus group first?
(3) Narrow, tight questions. Once you have formulated a question, narrow it down in a focused way so that you can carry out the research in a short period of time. Look at the class slide in which we taked about different ways to narrow down a question.
(4) Feasibility. Just because you have the question, and just because it might be relevant, doesn't mean you can carry it out in 10 or so weeks. Remember, that's basically all you have. Think about such details as getting the data (sample size, recruitment), inputing data (complex surveys take time to input), analyzing the data, writing up the results, preparing the work for presentation.
(5) Theory. Don't forget to answer the because question. Your question and hypothesis need to be grounded in a theory. The theory arises from understanding the literature that you have gotten from your literature research and then subsequently have read. For example, you might say something like this - "I think that self-reported quality of life (as measured by the ABCD QOL scale) in African-American female nursing home residents over the age of 75 years will be better than a comparable age-matched Caucasian group because, in a similar study of .... by Jakobs and Lee (1999), they found that ..."
(6) Hypotheses. Remember, a hypothesis statement contains two parts, H0 - the hypothesis of no change and HA - the hypothesis of change. Hypotheses are necessary in order for us to ask highly focused questions that are then testable using statistical methods. As you progress from your general question to a narrower question to a theory and hypothesis, use the material in class to guide you so that you have a tightly focused hypothesis statement.
(7) Continue to carry out your literature review. Now that you are focusing, you may want to consider revisiting the literature to obtain articles that more reasonably address the focused questions you are forming. Remember, Ovid allows you to make merges/joins in queries. You may now wish to make use of that feature to help you obtain the literature you will need.