Please post your question, quote, and fact here for chapter 7. Also, please respond to at least two of your peers' posts and answer my questions.
Questions:
1.) What is the process of preparing and organizing your data for analysis?
2.) How do you analyze descriptive research questions?
3.) How do you analyze hypotheses and inferential research questions?
4.) Why are tables, figures, and a results section significant?
5.) Describe a discussion section of a research report.
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1. The process of preparing and organizing your data for analysis consists of scoring the data and creating a code book, determining the types of scores to use, selecting a computer program, inputting the data into the program for analysis, and clearing the data.
ReplyDelete2. Some questions may call for describing trends in the data, and the researcher uses descriptive analysis such as measures of central tendency, the spread of the scores, and the relative ranking of the scores.
ReplyDelete3. Other research questions and hypotheses call for inferential analysis in which the researcher studies a sample and draws inferences from the sample to a population. To conduct inferential analysis, three procedures might be used;
ReplyDelete1. Conduct hypothesis testing by using statistical tests and calculating p values that are determined to be significant or nonsignificant, and suggest that the sample mean is or is not a good estimate of the population mean.
2. Set a confidence interval to identify a range of scores that is likely to include the population mean.
3. Calculate an effect size that examines the strength of the differences and the practical meaning of these differences for group comparisons or relating variables.
4. One advantage of using tables is that they can summarize a large amount of data in a small amount of space.
ReplyDeleteA good figure:
1. Augments,rather than duplicates, the text
2. Conveys only essential facts
3. Omits visually distracting detail
4. Is easy to read and understand
5. Is consistent with and is prepared in the
same style as similar figures in the same
article.
6. Is carefully planned and prepared
For descriptive statistics, the means, standard deviations, and the range of scores show useful information about results. For inferential statistics, information such as the alpha level used, the actual p value, the critical region of rejection, the test statistic results, the degrees of freedom, and effect size should be reported. Confidence intervals should also be reported.
5. Researchers conclude a study by summarizing key findings, developing explanations for results, suggesting limitations in the research, and making recommendations for future inquiries.
ReplyDeleteFact: If we collected sample after sample of scores and plotted them on a graph, they would look like a bell-shaped curve.
ReplyDeleteQuote: "When the critical region for rejection of the null hypothesis is divided into two areas at the tails of the sampling distribution, we have a two-tailed test of significance. However, if we place the region at only one end for rejection of the null hypothesis, we have a one-tailed test of significance.
Question: How effective are bar charts, scatterplots, line graphs, and charts used for data results in research?
1.) What is the process of preparing and organizing your data for analysis?
ReplyDeleteA:
Preparing and organizing data for analysis consists of scoring the data and creating a codebook, determining the types of scores to use, selecting a computer program, inputing the data into teh program for analysis, and clearing the data.
2.) How do you analyze descriptive research questions?
A:
You have to address each on of your research question in your analysis.
You have to describe trends in the data to a single variable or question on your instrument. You can show the statistic or comparison. We can decribe our variables in data analysis.
3.) How do you analyze hypotheses and inferential research questions?
A:
We present the result in table, figures, and discuss in detail of the results. We may provide the explaination base on our prior predictation. We can explain the limitation of our research and may suggest the way to develop the research in the future.
4.) Why are tables, figures, and a results section significant?
ReplyDeleteA:
They are summarize our data in graphic(picture or image), which are easy to understand and organize. Moreover, they can help us to analize and make conclusions for our research.
5.) Describe a discussion section of a research report.
A:
We summarize the major results of our study then explain why the result occure. We can discus the limitation in our researches and suggest how to improve the research in the future.
Additionally, in the question number 3.
ReplyDeleteI am sorry, I am a little bit overwhealmed.
How we analyze the hypotheses and inferential research?
1. Conduct hypothesis testing by using statistical tests and calculating p values that are determined to be significant or nonsignificant, and suggest that the sample mean is or is not good estimate of the population mean.
2. Set a conficence interval to identify a range of scores that is likely to include the population mean.
3. Calculate an effect size that examines the strength of the differences and the practical meaning of these differences of group comparisons or relating variables.
I think I will have a break tonight. I will come back to finish it tomorrow.
ReplyDeleteGood job so far here!!!! Please let me know if you have any questions or concerns! I am here to help!
ReplyDeleteTo Dr. Hendrix, I have a question about the inferential research.
ReplyDeleteWhat is inferential research? I have a little bit confuse here with hypotheses.
Thank you.
1. The first step is to score the data and give it a numeric score. You have to select a numeric score for each response. A codebook is a list of variables and how the researcher will code or score responses.. The second step is to determine the types of scores to use. You have to decided if you are going to score items independently or if you are going to score all of the questions together. Then you have to select a Stat computer program. The one that I am most familiar with is SPSS, I think it is the most popular. Then you have to input the data into the program. And then you have to look for errors. This is easy to do when you are inputting data manually.
ReplyDelete2. There are 3 way s to analyze descriptive statistics, central tendency, variability, and relative standing. The measures of central tendency are mean, median, and mode. Mean is the average, mode is what occurs most often and median is the middle. All three of those are pretty easy to calculate. Variablitly is the range, variance, and standard deviation. The range is the difference between the highest and lowest numbers or scores. Variance is the dispersion of scores around the mean, and standard deviation is the square root of the variance. These give us our normal bell curve. Relative standing compare one score to a group of scores. This gives us the percentile rank.
3. When you are comparing groups or relate two or more variables you need to use inferential statistics. Hypothesis testing compares an observed value of the sample population to determine if there is a difference or no difference (null hypothesis).Confidence interval is the range of upper and lower scores. Effect size tells us the strength of the differences that we obtain.
4. They are important because they summarize your findings, portray variables and explain statistical results. If someone who is not trained in statistical analysis is trying to read your study then they may not understand it. IF they can jump to a result section it may be easier for them to understand.
5. First you have to summarize the results. This is just a summary of the finding for each question or hypothesis. Then you have to explain why the results occur. This section may compare and contrast other studies to the current study. Then you have to identify problems that may have occurred with the study. This allows people the ability to generalize findings. Then you need to suggest future research. Based on your results you may have ideas for further studies.
Quote:
“Statistics can be challenging” pg 182 This is an understatement.
Fact:
Cleaning the data is the process of inspecting the data for scores that are outside the accepted range. I had never heard of cleaning the data before.
Question:
Has anyone found another program as good as SPSS that is cheaper or better yet free??
Helen,
ReplyDeleteI think bar graphs, scatterplots, and line graphs are a good visual aide. The allow the reader to get a visual picture of the data.
Jessica,
ReplyDeleteI guess it's like the saying, "A picture is worth a thousand words".
Prueksa,
ReplyDeleteLike you, I think qualitative research is simplier to understand than quanitative research. When I checked out the book, "Discovering Statistics using SPSS (Introducing Statistical Methods S.) by Andy Field which is 750 pages long, I found it to be very complex.
QUESTION:
ReplyDeleteIt seems to me that it would be a better idea to throw out the participant with missing data rather than to have the computer average the other data out for that question. Then I feel like the data is then scud and not as reliable if some of it is fabricated. Right? (Page 189)
QUOTE:
I liked all of the questions on page 198: “How many independent variable do you have in one research question or hypotheses?” all of these were great questions and I gained a lot through them and their answers.
FACT:
“If the null hypotheses is true the theoretical distribution would be approximate a normal or bell-shaped curve.” (Page 196)
I would definitely agree with Jessica and Helen. The pictures are worth a thousand words. I for one would be completely lost in most of our reading and reading for other classes if there weren't charts and visuals!
ReplyDeleteJessica,
ReplyDeletein regards to your fact: I had never hear of that either. What would you do just like the missing data. Are we just going to take the 6 as a very excited 5 or the 3 for the gender... would you just throw that out?
Chapter 7 Questions:
ReplyDelete1.) What is the process of preparing and organizing your data for analysis?
A) The process of preparing and organizing your data for analysis is to first Score the data: “assign a numeric score to each response category for each question on the instruments used to collect data.” (Page 183) a helpful procedure would be to create a codebook (“a list of variables or questions that indicated how the researcher will code or score responses from instruments or checklists.”), the next thing to do in preparing and organizing your data is to determine the types of scores to analyze. Determining the types of scores is very important because what every your choose will affect how you put data into the computer. (Page 184) Then you will need to select a statistical program. The hardest part of this step is deciding what program to use. The book gives lots of helpful hints on choosing a program that works for you. (Page 186-187). You will then need to Input Data. This “occurs when the researcher transfers the data from the responses on instruments to a computer file for analysis.” (Page 187) The next step in preparing and organizing you data is to clean and account for missing data. You need to look over your data in the computer and make sure that everything is correct and they you have accounted for all of your responses. Different things happen that mess up your data collection: questions are skipped; participants are absent the day of data collection. You need to account for this missing data and tell your reader what you did with the incomplete data so they can know all of the information before they read the data. (Page 189) The next step is cleaning the database “the process of inspecting the data for scores that are outside of the accepted range.” (Page 189) You need to make sure that you data are error free before you go to analyze the data. The last step is assessing the data for missing data “data missing in the database because participants didn’t supply it.” (Page 189) When there is missing data you can do one of two things: throw the participant with missing data out of the study, or have the computer come up with an average for that question. (Page 190)
Rebecca posted:
ReplyDelete2.) How do you analyze descriptive research questions?
A) When you are analyzing descriptive research questions you use statistics. You need to choose a descriptive statistics test to summarize the over all trends in your data to provide an overall understanding of your data and compare one piece of data to the rest of your data. (Page 191) Finding the mean, median, and mode of your data; range of scores; standard deviation, and measures of relative standing.
Rebecca posted:
ReplyDelete3.) How do you analyze hypotheses and inferential research questions?
A) When Analyzing inferential research questions you are looking at scores from a sample and use the results to draw inferences or make predictions about the population. (Page 195) You are then testing the hypotheses to see if the prediction made about the results by comparing an observed value of sample with a population value to determine if no difference or relationship exists between the values. (Page 195) “There are five steps to hypotheses testing: (a) identify a null and alternative hypotheses; (b) set the level of significance, or alpha level; (c) collect data; (d) compute the sample statistic; and (e) make a decision about rejecting or failing to reject the null hypotheses.” (Page 196)
Rebecca posted:
ReplyDelete4.) Why are tables, figures, and a results section significant?
A) Tables, figures, and a results section are significant because the help to show visually the different data and information in your study. The reader need the results section to know how your study turned out: was you hypotheses correct? And other important information about the statistical test. (Page 205)
5.) Describe a discussion section of a research report.
A) The discussion section of a research report is the sections that “provides a general summary of the results presented.” (Page 209) this is also a section that the author will reference other studies with similar findings, advance ideas for further research, and end on a positive note about the final importance of the results of the study. (Page 209)
Rebecca posted:
ReplyDeleteQUESTION:
It seems to me that it would be a better idea to throw out the participant with missing data rather than to have the computer average the other data out for that question. Then I feel like the data is then scud and not as reliable if some of it is fabricated. Right? (Page 189)
QUOTE:
I liked all of the questions on page 198: “How many independent variable do you have in one research question or hypotheses?” all of these were great questions and I gained a lot through them and their answers.
FACT:
“If the null hypotheses is true the theoretical distribution would be approximate a normal or bell-shaped curve.” (Page 196)
Rebecca,
ReplyDeleteWhen you take your statistics class with Dr. Edwards next summer, you will understand how the statistics work for situations like these, and then, I think that class with her will clear up a lot of questions like these. At times, if you have a small sample, taking out data will not be the answer. Also, in education, students move or are in transition, so you will not end up with the same no. you started out with a lot of times. The statistical analysis is set up to take all of this into account. They are reliable, and Dr. Edwards will teach you this part and how to use SPSS. This is the first class most of you have had on research, and you will build on it through the program. Ideally, if you can still do your study without that data, do that. Often, we have small numbers in our studies though. Think about that.
Keep up the good work class! I am seeing some depth in your questions and thinking here!!!
Prueksa,
ReplyDeleteThink about inferences as predictions. Then, look back at that section in the book. If this does not make sense then, shoot me an e-mail, and I will walk you through this.
Keep up the good work!
Prueksa,
ReplyDeleteDo not be overwhelmed! It is okay. This is a lot to take in during one, three-hour class. Get what you can, and we will keep building on it. You are doing well! In the class videos, I am telling them the same thing. There is a fear with research, and it is intimidating. We are here to help you though! Your committee and chair will help guide you through the process.
Keep up the good work!
1. The process consists of assigning numeric scores to each response option on instruments; determining whether single item , net, or difference scores will be used; and selecting computer software to analyze the data. Next, the investigator enters the data into the computer and begins the process of analyzing.
ReplyDelete2. The researcher uses descriptive analysis such as measures of central tendency, the spread of the scores, and the ranking of the scores.
3. a.Conduct hypothesis testing by using statistical tests and calculating p values that are determined to be significant or non significant, and suggest that the simple mean is or is not a good estimate of the population mean. b.Set confidence interval to identify a range of scores that is likely to include a population of the mean. c.calculate an effect size that examines the strength of the differences and the practical meaning of these differences for group comparisons or relating variables.
4. Tables can store a large amount of data in a small amount of space. Figures are good for presenting information in graphs and pictures.
The results describe detailed results of the tests.
5. The discussion report summarizes key findings, develops explanations for results, suggests limitations in the research, and makes recommendations for future inquiries.
Fact: A standard score is a calculated score that enables a researcher to compare scores from different scales.
Quote: "You need to examine your database for missing data." p.189
Question: How difficult was it to analyze data before computers?
Matt,
ReplyDeleteIt was very time consuming and laborious! We are so thankful that we have computer programs to help here now!
Keep up the good work!
1.) What is the process of preparing and organizing your data for analysis?
ReplyDeleteFirst the researcher scores the data by assigning a numeric score to each response category for each question that the instrument used to collect data. A codebook is a procedure that aides to assigning scores. Next the researcher determines the type of score to analyze, single item scores, summed scores, or difference scores. After scoring the data, the researcher chooses a computer program to analyze the data, and then inputs the data by transferring it from the responses on instruments to a computer file. The last step is cleaning the database by inspecting it for scores outside of the accepted range and then examining the database for missing data.
2.) How do you analyze descriptive research questions?
First you choose a descriptive statistics tests that will help you summarize the trends in the data, an idea of the variability on the data, and insight into where the score stands against others. This is done by three separate measures. The measures of central tendency that are a summary number that in a distribution of scores represent a single number. The measures of variability indicates the spread of the scores in a distribution. Also, the measures of relative standing describe one score relative to a group of scores.
3.) How do you analyze hypotheses and inferential research questions?
There are several approaches for determining if the sample scores are a good representation of the population’s score. First perform hypothesis testing by comparing an observed value of a sample with a population value to determine whether or not to accept or reject the null hypothesis. Next, researchers estimate the confidence intervals. This looks at the range of upper and lower statistical values and is likely to have the actual population mean in the range. Last, it is important for researchers to know the strength of the difference between two variables. The effect size is determined by looking at the differences and determining whether the difference is meaningful.
4.) Why are tables, figures, and a results section significant?
ReplyDeleteResearchers use tables, figures, and the results section to represent the data from the statistical tests in a concise way and to respond to the hypothesis or each research question one by one with the statistical data. A table is used to summarize statistical data organized into rows and columns. Figures represent the statistical data in in graphs or visual aides, such as bar charts, scatterplots, line graphs, or charts. The results section is used to describe in detail the results of the statistical tests by summarizing each statistical test into one or two sentences.
5.) Describe a discussion section of a research report.
The discussion section concludes a study by first summarizing the major results to each research question or hypothesis and suggesting positive implications of the study. Nest the researcher explains why the results occurred by comparing the results to theories or other bodies of literature. Researchers should also list the limitations, or potential weaknesses of the study, one by one to recommend future studies and to help the reader determine the extent to which the findings can be generalized. The last step of the results section is to suggest future research directions based on the results of the study.