PSYC FPX 4700 Assessment 1 Basics Of Research And Statistics

SYC FPX 4700 assessment 1 Complete the following problems within this Word document. Do not submit other files. Show your work for problem sets that require calculations. Ensure that your answer to each problem is visible. You can highlight your answer or use a different type color to set it apart.

Problem Set 1.1: Identifying Variables (Dependent, Independent, Quasi-Independent)

Criterion: Identify dependent and independent variables.

Instructions: For the following examples, identify the dependent and independent (or quasi-independent) variables.

1. A researcher tests whether cocaine use increases impulsive behavior in a sample of cocaine-dependent and cocaine-inexperienced mice.

Independent Variable:  Cocaine use

Quasi-Independent Variable: Cocaine dependency status (cocaine-dependent vs. cocaine-inexperienced)

Dependent Variable: Impulsive behavior

2. A professor tests whether students perform better on a multiple-choice or fill-in-the-blank test format.

Independent Variable:  Test format

Quasi-Independent Variable: None

Dependent Variable: Test performance

3. A researcher tests whether smoking by parents influences children’s attitudes toward smoking behavior.

Independent Variable: Smoking by parents

Quasi-Independent Variable: None

Dependent Variable: Children’s attitudes toward smoking behavior

4. A social scientist tests whether attitudes toward morality differ based on political affiliation (Democrat or Republican).

Independent Variable: None

Quasi-Independent Variable: Political affiliation

Dependent Variable: Attitudes toward morality

5. A cultural researcher tests whether individuals from different cultures share or differ in the belief that dreams have meaning.

Independent Variable: None

Quasi-Independent Variable: Culture

Dependent Variable: Belief that dreams have meaning

Problem Set 1.2: Understanding Sample and Population

Criterion: Describe the relationship between population and sample.

Instructions: Read the following and answer the question.

Height and educational attainment: Szklarska et al. (2007) hypothesized that taller young men are more likely to move up the scale of educational attainment compared with shorter individuals from the same social background. They recruited 91,373 nineteen-year-old men to participate in the study.

Do these participants most likely represent a sample or population? Explain.

These respondents likely form a sample. Although the 91,373 respondents were numerous, they constituted just a part of the far greater population of all men at age nineteen. A sample is a smaller, workable subset of a population, enabling researchers to make inferences regarding the population. In this case, researchers have studied a group of nineteen-year-old men about their height and educational attainment, but the group is unlikely to include all the nineteen-year-old men of the world. So it is a sample group through which generalization of findings may be made to the larger population of young men.

______________________________________________________________________________

Problem Set 1.3: Create a dataset for use in JASP

Criterion: Enter and display data for use in JASP.

Data: Five social media users spent the following number of minutes viewing Twitter:
15.21, 46.18, 12.45, 65.486, 26.852.

Instructions: Use the supplied data to complete the steps below.

1. Open Excel.
2. In cell A1, type Minutes. The variable of Minutes is continuous.
3. In cells A2-A6, enter the supplied data in the column labeled Minutes.
4. Save your dataset as a .csv file
5. Open JASP.
6. In the sandwich menu, scroll down to OPEN, then select COMPUTER. Locate your .csv file and click it to open it.
7. Take a screenshot of your data in JASP and paste it below.

Table 1

Problem Set 1.4.a: Grouped or Ungrouped

Criterion: Explain the identification of types of data.

Instruction: Fill in the table below. For each example, state whether it is grouped or ungrouped and why.

Example	Grouped or Ungrouped	Why
The time (in seconds) it takes 100 children to complete a cognitive skills game.	Ungrouped	The data consists of individual time measurements for each child. Each time value is distinct and not grouped into categories or intervals.
The number of single mothers with 1, 2, 3, or 4 children.	Grouped	The data is grouped into categories (1, 2, 3, or 4 children). The numbers represent counts of single mothers in each category, rather than individual data points.
The number of teenagers who have experimented with smoking (yes, no).	Grouped	The data is grouped into categories (yes, no) representing the number of teenagers in each category. It shows counts of teenagers within those groups rather than individual data points.
The age (in years) of freshman students in a local college.	Ungrouped	The data consists of individual age values for each freshman student, with no categories or intervals used to group the data. Each student’s age is a specific, distinct value.

Problem Set 1.4.b: Understanding Descriptive and Interferential Statistics

Criterion: Explain the identification of types of data.

The two primary classifications for datasets are grouped and ungrouped data:

• Grouped Data: Grouped data is when data is organized into intervals or categories, such as age ranges (e.g., 20-30, 30-40) or counts within categories (e.g., 1 child, 2 children). It is a summary of large datasets, which makes it easier to interpret and analyze trends.
• Ungrouped data contains individual data points which are not grouped into any intervals or groups. It represents each value as an individual observation, such as the exact age of the people or the exact score of the participants. This data provides detailed information but is more complicated to analyze when there is a large number of observations.

Instructions: Read the following and answer the question.

Gun ownership in the United States: Data from Gallup polls over 40 years show how gun ownership in the United States has changed. The results are described in the table below, with the percentage of Americans who own guns given in each of 5 decades:

Year	%
1972	43
1982	42
1992	48
2002	40
2012	43

Source: Reported at http://www.gallup.com/poll/1645/Guns.aspx

1. Are the percentages reported here an example of descriptive statistics or inferential statistics?

Descriptive statistics summarize or describe the characteristics of a dataset. Here, it sums up or describes the percentage of Americans who own guns over 40 years. Percentages obtained are of the observed data and don’t predict or infer anything regarding a population greater than that surveyed.

Based on the percentages given in the table, how has gun ownership in the United States changed over the past 40 years?

Based on the percentages in the table, gun ownership within the United States has increased and decreased over the last 40 years.

2. In the year 1972, 43% of the Americans owned guns.
3. Gun ownership slightly decreased to 42% in 1982.
4. In 1992, it increased to 48%, the highest over the 40 years
5. In 2002, it dropped to 40%, the lowest percentage over the 40 years.
6. By the year 2012, it had risen again to 43%, the same level as that of 1972.

Gun ownership displayed some variation over time – peaking in 1992 and at an all-time low in 2002-but otherwise fluctuating between about 40 to 43 percent of Americans for most of the last thirty years.

Problem Set 1.5: Reading a Chart

Criterion: Locate data on a chart.

Instructions: Read the following and answer the questions.

Participant CharacteristicsProfession	Count
	Type	Token
College ProfessorClinical PsychologistUnknown	24,54123,617479	878,261751,188927
Total		1,630,376

1. Do college professors or clinical psychologists in this sample speak more words overall (Token Count)?

Clinical psychologists in this sample speak more words overall (Token Count).

• College Professors: 878,261 tokens
• Clinical Psychologists: 751,188 tokens

The Token Count for college professors is 878,261 versus 751,188 for clinical psychologists; therefore, college professors utter more words overall.

2. Do college professors or clinical psychologists in this sample speak more different words (Type Count)?

College professors in this study use more unique words as a whole (Type Count).

• College Professors: 24,541 types
• Clinical Psychologists: 23,617 types

The type count for college professors is 24,541; the count for clinical psychologists is 23,617, suggesting that college professors use more different words.

Problem Set 1.6: Frequencies and Percentages

Criterion: Identify frequencies and percentages.

Instructions: State whether a cumulative frequency, relative frequency, relative percent, cumulative relative frequency, or cumulative percent is most appropriate for describing the following situations. For cumulative distributions, indicate whether these should be summarized from the top down or from the bottom up.

Data: 

1. The frequency of businesses with at least 20 employees: Cumulative Frequency (from bottom up)
2. The frequency of college students with less than a 3.0 GPA: Cumulative Frequency (from the bottom up)
3. The percentage of women completing 1, 2, 3, or 4 tasks simultaneously: Relative Percent
4. The proportion of pregnancies delivered in public or private hospitals: Relative Frequency
5. The percentage of alcoholics with more than 2 years of substance abuse: Cumulative Percent (from bottom up)

Problem Set 1.7: Understanding Percentages

Criterion: Identify distribution type and number of people.

Instructions: Read the following and answer the questions.

Perceptions of same-sex marriage: In June 2016, a CBS News poll asked a sample of adults worldwide whether it should be legal or not legal for same-sex couples to marry (reported at http://www.pollingreport.com). The opinions of adults worldwide were as follows: 58%, legal; 33%, not legal; and 9%, unsure/no answer.

1. What type of distribution is this? This is Categorical Distribution.
2. Knowing that 1,280 adults were polled nationwide, how many Americans polled felt that same-sex couples should be allowed to legally marry? 742 Americans

Problem Set 1.8: Create an Ascending Frequency Table in JASP

Criterion: Create an ascending frequency table in JASP.

Data: Use dataset clicks. jasp. This dataset is a record of the number of clicks per hour in forty different tweets.

Instructions: Complete the steps below.

1. Download clicks. jasp. Double-click the icon to open the dataset in JASP.
2. In the Toolbar, click Descriptives.
3. Select Clicks and then click Arrow to send it over to the Variables box.
4. Click Tables. In the menu that opens, check Frequency Tables.
5. Copy and paste the ascending values frequency table into the Word document.

Note: You will continue to use this dataset in the next two problems.

Table 2

Frequency Table for Clicks

Clicks	Frequency	Percent	Valid Percent	Cumulative Percent
0	5	12.5%	12.5%	12.5%
1	8	20%	20%	32.5%
2	10	25%	25%	57.5%
3	7	17.5%	17.5%	75%
4	6	17.5%	17.5%	85%

Problem Set 1.9: Construct a Bar Graph in JASP

Criterion: Construct a bar graph in JASP.

Data: Use dataset clicks. jasp. This dataset is a record of the number of clicks per hour in forty different tweets.

Instructions: Complete the following steps to create a bar chart to examine the data:

1. Download clicks. jasp. Double-click the icon to open the dataset in JASP.
2. In the Toolbar, click Descriptives.
3. Select Clicks and then click Arrow to send it over to the Variables box.
4. Click Basic Plots, then check Distribution Plots.
5. Copy and Paste the bar graph below.
6. Optional to answer: What is the shape of the distribution? Skewed (or Normal, depending on the data).

Note: You will continue to use this dataset for the next problem.

Table 3

Problem Set 1.10: Construct a Pie Chart in JASP

Criterion: Construct a pie chart in JASP.

Data: Use dataset clicks. jasp. This dataset is a record of the number of clicks per hour in forty different tweets.

Instructions: Complete the following steps to create a pie chart.

1. Download clicks. jasp. Double-click the icon to open the dataset in JASP.
2. In the Toolbar, click Descriptives.
3. Select Clicks and then click Arrow to send it over to the Variables box.
4. Click Basic Plots, then check Pie charts.
5. Copy and paste the pie graph below.

Table 4