Complete the following:
Review Research Methods & Basic Statistics
Q1. Briefly describe your area of research interest (1-3 sentences is sufficient).
My reseach area is to test the hypothesis to see if playing violent video games have an effect on adolscent behavior.
Q2. List 4 variables that you might assess in a research project related to your research area. List one for each type of measurement scale:
Nominal, ordinal, interval, and ratio. If you cannot think of a variable for each measurement scale, explain why the task is difficult.
Question: What types of games are interesting? (Violence, rated PG, rated G)
Nominal Variable: Type of games that interest a person.
Question: Do the graphics in violent video games? (Yes, not very much, they are ok. A lot)
Ordinal Variable: Opinions toward violent video games.
Interval or Continuous Variable: Behavior is measured by aggressiveness.
Aggression is measured on a scale from 1 to 5. The difference between 2 and 3 is the same as 4 and 5.
Ratio Variable: Aggression measured in Males. 0 Males are often called absolute zero which indicates there is no aggression what so ever.
Q3. Create one alternate hypothesis and its associated null hypothesis related to your research area.
Hypothesis 1: Exposure to video game violence in a controlled environment results in increased aggression?
Hypothesis 2: Adolescent who is exposed to more violent video games in real life are more prone to aggressive behavior.
Q4. Briefly describe whether you think your area of interest is more conducive to experimental or correlational research. What are the costs/benefits of each as it relates to your research area?
A. correlational design is used to examine the prediction if there is a relationship between exposure to faviolence, personality and trait aggression, video-game playing habits, and violent crime commission
B. In an experimental design, a participant is randomly assigned to one of the three groups. This design provides a test of whether participants' perspective of personal responsibility for playing a violent video game produced different behavior effects from randomization.
C. Participants will also be asked to report their real-life exposure to violent video games
From the two hypotheses provided, I believe experimental will be more conducive to my research.
Q5. Reliability vs. Validity. Considering your area of research interest, discuss the importance of reliability and validity. Can you have one without the other? Why or why not?
Reliability is the degree of producing stable and consistent. or the degree to which an assessment tool produces stable and consistent results.
Validity refers to how well a test measures what it is purported to measure.
In my area of research reliability cannot work without validity. It is vital to use both validty and reliability to have a positive outcome.
Q6. Sample vs. Population. Considering your area of research interest, describe the difference between a sample and population. Why is it important to understand the difference between a sample and population in a statistics course?
A population: consists of all data or collection of similar objects.
Sample consists of some data from the full data or group.
For example: You want to know if male adolescents who play violent video games on a regular bases have an increase in aggressive behavior. The participants involved consist of all male adolescents attending LSC. Only 100 of the participants was randomly chosen to participate in a survey.
All the male adolescent in LSC is the population and the 500 participates is the sample.
Q7. Measures of Central Tendency. Below is a set of data that represent weight in pounds for a particular sample. Calculate the mean, median and mode. Which measure of central tendency best describes this data and why? You may use Excel, SPSS, some other software program, or a hand calculator for this problem.
110.00
117.00
120.00
118.00
104.00
100.00
107.00
115.00
115.00
115.00
114.00
100.00
117.00
115.00
103.00
105.00
110.00
115.00
250.00
275.00
Mode = 115
The data tells me that, the median (the middle number) is 115. From the same data, you can see that 115 is the only number that occurs more than once. So, the mode is 115. It can be said that it is true because the average is 126.25 define to be the mean. However, of the three measures of central tendency Mean: 126.25, Median: $115, Mode: 115, looking at the median it is clear that it is the most irepresentative. The mean is inflated by the two highest numbers.
Q8. Measures of Dispersion. For the data set above, calculate the range, the interquartile range, the variance, and the standard deviation. What do these measures tell you about the "spread" of the data?
Range 175
Minimum 100
Maximum 275
Rearranging the list above in a range from 100 - 275. The range is equal to the difference between the maximum and minimum value. Therefore, the range = 275-100 = 175.
Hypothesis test results:
σ2: Variance of variable
H0 : σ2 = 1
HA : σ2 ≠ 1
Variable Sample Var. DF Chi-Square Stat P-value
var1 2224.5132 19 42265.75 <0.0001
The measures tell us about the variation in the data. From range (175) we can see that there is as huge difference between minimum 100 and maximum (275) values. Also, from variance and standard deviation (47.165) we can easily see that the data is widely spread as standard deviation is very large.
Q9. Descriptive Statistics. Why is it important to perform basic descriptive statistics prior to conducting inferential statistical tests?.
Descriptive statistics helps to summarize the raw data. Whereas, inferential statistical tests are used to draw conclusions about the population by using sample data. Inferential statistical test are based on the normality or non-normality of the data. If there is regularity in the data, then we will proceed with parametric inferential statistical tests. If there is no consistency in the data, then we will proceed with non-parametric inferential statistical tests. To perform the parametric inferential statistical tests, we must know the population (sample) mean and population (sample) standard deviation as per the test statistics. Therefore, it is important to perform basic descriptive statistics prior to conducting inferential statistical test.
Q10. Statistical Significance. Revisit the hypotheses you created above in #5. If you conducted a statistical test based on these hypotheses and found a statistically significant result, what would that mean from both a statistical and practical standpoint? (Be sure to use the phrases "null hypothesis" and "effect size" in your answer).
If I found a statistically significant result (p-value is less than 0.05) then I will reject the null hypothesis and accept the alternative hypothesis. This means that the results I want to prove using our alternative hypothesis is true and valid.
Q11. Type I and Type II Error. The concept of Type I and Type II Error is critical and will come into play not only with each and every statistical test you perform, but when you are asked to conduct an a priori power analysis for your Dissertation Proposal. Considering your answer to #10, discuss the implications of making both a Type I and Type II error.
When you reject the null hypothesis knowing that it is true, you have made a Type I error. When you accept the null hypothesis knowing that it is false, we made a type II error. Type I error is always fixed at some level, and the researcher always try to reduce the type II error so that the power of the test can increase.