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Statistics and Research
1. Have any of your peers, colleagues, or instructors ever stated that a study “proves” something? If so, briefly describe what he or she said, and in light of reading the materials provided, would you be cautious about believing such a statement? Why? (answer in one-two paragraphs)
One of my peers believes that indeed, a study has the ability to prove something. According to him, undertaking a study enables a researcher to explore all the facts and provide vital information that then enables them to prove the fact or hypothesis. In addition, he stated that undertaking a study enables one to gain more insight about the subject under review and perhaps generate more information that can then be employed in proving the respective hypothesis. From an individual point of view, I would be cautious about believing the statement. Not every study proves a hypothesis. Depending on the manner in which the hypothesis is stated, the findings of some studies disapprove the hypothesis. The complex and dynamic environmental changes have diverse implications on the wellbeing of the various phenomena. The inherent dynamism during the course of the study can alter findings at any time. In this respect, a study does not always prove something.
2. According to the reading materials, what is the primary and secondary purpose for preparing a literature review?
The primary purposes of the literature review are to explore whatever has already been done in light of the research problem and to identify research strategies as well as specific measuring instruments and procedures that can be effectively employed in undertaking the current research. Secondary purposes of the literature review include: to broaden the knowledge in this area of study, to identify any opposing view points, to provide a definition of the major concepts and be able to measure them and to prevent reinvention of the wheel.
3. What do quantitatively oriented researchers emphasize when sampling that qualitatively researchers do not emphasize?
Unlike qualitative researchers, quantitative researchers place great emphasis on the accurate prediction of the sample size during sampling.
4. Name two examples of common sampling flaws.
Sample error and bias
5. Name a trait, other than the ones mentioned in this chapter that you think are inherently difficult to measure. Why? Frustration is a trait that may be difficult to measure during research. This is due to the fact that it is highly subjective and can not be easily quantified.
6. Briefly explain why a highly reliable measuring instrument can be invalid. This may not be consistent with the methods or techniques of research
7. If a common well-known IQ scale is considered to have adequate reliability and validity, does this mean the scale has no flaws? No. If not, briefly explain why. This is because it is likely to be influenced by the external factors contributed to by the researcher. The scale used in rating does not also provide distinct measurements.
8. To study causality, what do researchers need to do? Why? They need to establish the relationships between different factors. This is because causality implies that one event has an effect on another event.
9. If a difference is statistically significant, does this mean the difference is large? No. If not, what does the fact that a difference is statistically significant tell you? This implies that the respective difference did not occur solely by chance. What else can you look at to indicate the magnitude of a difference? Correlation between the variables
10. Provide examples of the following using variables and a made up correlation to illustrate your point: a. Strong positive (direct) correlation Construct your response like the example given here: A strong positive correlation exists between study time and GPA (r = .74). That is, as study time increases so does GPA.
b. Weak positive correlation
A weak positive correlation exits between job satisfaction and helpfulness (r= 26). That is, as job satisfaction increases, helpfulness tendencies increase slightly.
c. Strong negative (inverse) correlation
There is a strong negative correlation between education and imprisonment (-72). That is educated individuals are unlikely to be imprisoned.
d. Weak negative correlation
There exists a weak negative correlation between being held and crying (-25). That is, babies that are held are unlikely to cry.
11. Considering a one-way ANOVA answer the following:
a. Name two assumptions
Samples are independent
The population variances are equal.
b. Define the terms
The first term found in the numerator is referred to as raw sum of squares while the second term is defined as the correction term for the mean
c. Why would a violation of these assumptions affect your results? Because the ANOVA procedure is very complex.
12. The Huck text indicates several Warnings about Correlations. One of the warnings is called an Outlier. What is an outlier and describe how this concept can affect the results of a correlational analysis. Outliers refer to uncommon or infrequent observations. Because of the manner in which a regression line is established and determined, outliers greatly impact on the slope of the particular regression line. As a result, it also influences the value of the respective correlation coefficient. Seemingly, a single outlier has the ability of altering the slope as well as value of the particular regression significantly.
13. State the three most common Central Measures of Tendency and provide a definition for each.
Mean refers to the sum of all the numbers in a set divided by the number of the numbers in the particular set of data. It is also referred to as the average.
Median: This represents the number that assumes a middle position when all the numbers in a particular set of data are organized or arranged in either a descending or ascending manner. In instances where the number of the particular numbers in the particular data set is even, the median is found by finding the average of the two numbers in the middle of the data set.
Mode: This refers to the value in the set of data that occurs more frequently.
14. What does it mean to say all the scores in the class are Negatively Skewed? Provide an example to illustrate the point.
15. What does it mean when a researcher states the population or sample is considered to be Homogeneous?
A homogeneous sample or population has participants with similar characteristics with respect to the variable that the researcher employs.
16. What does it mean when a researcher states the population or sample is Heterogeneous?
A heterogeneous sample or population constitutes participants that have different characteristics.
17. What is the general difference between a non-parametric and a parametric statistical test?
Whereas a parametric test is based directly on the statistics that are derived from a type of distribution with parameters like normal distribution, a non parametric test is simply based on rules of counting and probability as opposed to distributions.
18. If a researcher wanted to determine the strength and direction between two variables, then what type of analysis would he or she use? Why? In this regard, the researcher would use the Pearson’s r analysis or measurement. This is because it is useful in determining the direction as well as strength of linear correlation apparent between two ratio level or interval variables.
19. If a researcher was interested in determining the mean differences between three or more variables, then what type of analysis would he or she use? Why?
The analysis of variance would be the most ideal because of the fact that its process reduces the probability of committing errors.
20. Define the following:
a. Null Hypothesis
This represents a theory that is put forth because it is believed by the researcher to be true or because it is to provide the basement for the argument although it is yet to be proven.
b. Alternate Hypothesis
This presents a statement that a statistical hypothesis test is supposed to establish.
21. What does r2 mean and why would a researcher be interested in this index? R2 is also referred to as a coefficient of determination and it represents the proportion of variability inherent in a given data set that is also accounted for by a distinctive statistical model. Researchers need to be concerned about this index because it provides vital information regarding the goodness of fit of a given model.
22. What is Statistical power and why would a researcher conduct a power analysis prior to conducting a study? Statistical power refers to a percentage or number that underscores the probability of a study obtaining an effect that is statistically significant. Researchers are required to conduct a power analysis prior to research in order to establish viable estimates of sufficient sample sizes that would be able to attain adequate power.
23. Define Practical Significance. This refers to an arbitrary limit at which an observed difference has some degree of practical importance in real life situations.
24. Focus groups are often used to collect data for program evaluations. What are some common issues that a researcher should be aware of concerning focus groups? The researcher should be aware that focus group sessions need to be moderated accordingly to enhance optimal output. The moderator should provide direction in order to get the information that s/he needs. This is because in some instances, the focus group discussions generate general rather than specific information regarding the research question.
25. In program evaluation there is a type of evaluation called Process evaluation. What is another name for Process evaluation? Formative evaluation
Bonus Question: A researcher is looking at multiple explanatory variables (e.g., questions on a test) and he would like to determine the probability of inclusion each variable has in a specific category (i.e., easy, difficult, very difficult). The outcome variables or response variables are dichotomous (i.e., right or wrong). What is the most appropriate statistical technique? Logistic regression
