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PSYC FPX 4700 Assessment 5 Research Report

PSYC FPX 4700 Assessment 5 Research Report Free Sample Papers Anxiety (1) BS Psychology (107) Depression (11) Essay (2) Need writer for your Psychology Papers? Get your paper in 24 Hours. We have a team of Psychology Academic Writers who can help you quickly write plagiarism-free papers, essays, and research articles. Hire Writer PSYC FPX 4700 Assessment 5 Research Report Name Capella University PSYC FPX 4700 Statistics for the Behavioral Sciences Prof. Name Date Research Report The process of data analysis encompasses exploring, transforming, and modeling data to derive valuable insights, make informed conclusions, and facilitate decision-making (Kelley, 2020). It is extensively utilized to identify patterns and trends within datasets, thus providing crucial information for business strategies and decision-making processes. Nevertheless, to acquire meaningful insights, data necessitates undergoing cleaning, preparation, and transformation procedures (Cote, 2021). The present study delves into an examination of how student demographics, quiz, and final exam scores were documented by instructors across three distinct sections of a course. Data Analysis Plan Variable Scale of Measurement Quiz 1 Continuous GPA Continuous Total Continuous Final Continuous Variable 1 (Quiz), Variable 3 (Total), and Variable 4 (Final) are continuous variables because they can take any numerical value within a range. For example, Quiz scores can range from 0 to the maximum number of questions on the quiz, and Final exam scores can range from 0 to the maximum number of questions on the final exam. Variable 2 (GPA) is also a continuous variable, although it is typically measured on a categorical scale, such as a letter grade (e.g., A, B, C, D, F) or a numerical scale (e.g., 0-4.0). This is because GPA is calculated as an average of grades earned across multiple courses, which can take any numerical value within a range. State your research question, null and alternate hypothesis Is there a significant difference in the mean quiz scores across the three sections of the course? Null Hypothesis: There is no significant difference in the mean quiz scores across the three sections of the course. Alternative Hypothesis: There is a significant difference in the mean quiz scores across the three sections of the course. Testing Assumptions Variable N Minimum Maximum Mean Std. Deviation Skewness Kurtosis quiz1 105 0 10 7.47 2.481 -.851 .236   gpa 105 1.08 4.00 2.862 .71266 -.220 .236   total 105 54 123 100.09 13.427 -.757 .236   final 105 40 75 61.84 7.635 -.341 .236   Valid N (listwise): 105 Summarize whether or not the assumption is met. In assessing the normality of the data, we examine the skewness and kurtosis values. A perfectly normally distributed variable has a skewness of 0 and a kurtosis of 3. Hence, data with skewness and kurtosis values close to 0 and 3, respectively, are considered to be normally distributed. For instance, the Quiz variable exhibits a negative skewness and a kurtosis value of 0.162, indicating a slight leftward skew and a slightly higher peak than a perfectly normal distribution. Nonetheless, the magnitude of these values is relatively small, suggesting that the assumption of normality is not severely violated. Results and Interpretation | | quiz1 | gpa | total | final | |——-|——-|——-|——-|——-| | quiz1 | 1 | .152 | .797**| .499**| | gpa | .152 | 1 | .318**| .379**| | total | .797**| .318**| 1 | .875**| | final | .499**| .379**| .875**| 1 | According to the inter-correlation matrix, the correlation between quiz 1 and GPA is not statistically significant. The observed correlation coefficient is 0.152 with a p-value of .121, indicating a weak relationship between these variables, which is not deemed statistically significant. Additionally, the effect size is small, with a value of 0.05. Therefore, we do not have sufficient evidence to reject the null hypothesis. Conversely, a significant positive relationship is observed between the Total Score and the Final Score. The correlation coefficient is highly significant with a p-value of less than 0.001, allowing us to reject the null hypothesis for this correlation. PSYC FPX 4700 Assessment 5 Research Report Furthermore, when analyzing the correlation between the student’s GPA and final exam score, a Pearson Correlation coefficient of 0.379 was observed. This correlation is highly significant with a two-tailed significance level of less than 0.001 and is considered to have a moderate effect size. The moderate effect size indicates a moderate degree of association between GPA and final exam scores, suggesting a meaningful relationship between these two variables in the sample of 105 students. Statistical Conclusions Provide a brief summary of your analysis and the conclusions drawn. The analysis conducted on the data indicated a statistically significant difference in the mean quiz scores among students across the three sections of the course. This finding was further supported by a Pearson Correlation analysis, which revealed a strong and statistically significant correlation between quiz 1, total scores, and final scores. However, it is worth noting that the correlation between quiz 1 and GPA was not found to be statistically significant, indicating a weak relationship between these two variables. Moreover, it is essential to recognize that correlation analysis assesses association between variables and does not establish causality. While the significant correlations provide valuable insights into the relationships between the variables, they do not imply causation. Thus, further research or experimental studies would be required to explore any causal connections between the variables in question. Analyze the limitations of the statistical test The limitations of the statistical test used in the analysis include limited generalizability due to the specific sample studied, a limited scope of variables examined, assumptions of normality that may not hold for all variables, and a focus on correlation rather than causality. Provide any possible alternate explanations for the findings and potential areas for future exploration Future research has the potential to investigate various avenues for further exploration. For instance, understanding how student demographics or instructional strategies impact quiz scores could provide valuable insights. Additionally, by increasing the sample size, researchers can achieve greater precision in evaluating the relationships between variables (Vasileiou et al., 2018).

PSYC FPX 4700 Assessment 4 Anova Chi Square Tests and Regression

PSYC FPX 4700 Assessment 4 Anova Chi Square Tests and Regression Free Sample Papers Anxiety (1) BS Psychology (106) Depression (11) Essay (2) Need writer for your Psychology Papers? Get your paper in 24 Hours. We have a team of Psychology Academic Writers who can help you quickly write plagiarism-free papers, essays, and research articles. Hire Writer PSYC FPX 4700 Assessment 4 Anova Chi Square Tests and Regression Name Capella University PSYC FPX 4700 Statistics for the Behavioral Sciences Prof. Name Date ANOVA Exercise Set 4.1: Significance Threshold Criterion: Elucidation of the Relationship between k and Power Based on Calculated k Values Instructions: Work through the following exercise and write down the values observed in the F-table to gain familiarity with it. Level of Significance k = 2 k = 4 k = 6 k = 8 .05 ___ ___ ___ ___ .01 ___ ___ ___ ___ Analyzing the F-table: The F-table displays the degrees of freedom for the numerator (k − 1) across columns and for the denominator (N − k) across rows. Separate tables are provided for .05 and .01 levels of significance. As k increases (from 1 to 8), does the critical value increase or decrease? Substantiate your answer by explaining the relationship between k and power. Exercise Set 4.2: Analyzing Variance Unilaterally with JASP Criterion: ANOVA Calculation in JASP Data: Utilize the dataset stress.jasp, which records the fat consumption (in grams) among professional bodybuilders under various stress conditions. Instructions: Download stress.jasp and open it in JASP. In the Toolbar, select ANOVA under Classical. Choose Fat grams consumed and Stress level as Dependent and Fixed factors, respectively. Enable the Descriptive statistics option. Copy and paste the output. Exercise Set 4.3: Performing Analysis of Variance (ANOVA) Using Excel Criterion: ANOVA Calculation in Excel Instructions: Utilize the provided data to perform the following steps: Stress Levels         High Moderate Low 10 9 9 7 4 4 8 7 6 12 6 5 6 8 7   Label rows as High, Moderate, and Low. In the toolbar, select Data Analysis, choose Anova: Single Factor, and proceed. Specify Input Range as $A$1:$C$6, ensuring to check Labels in First Row. Copy and paste the output. Exercise Set 4.4: APA-Style Presentation of One-Way ANOVA Findings Criterion: Reporting ANOVA Results in APA Format Data: Utilize the results from the preceding exercise. Instructions: State the null hypothesis. Present the results in APA format, akin to a journal article. Exercise Set 4.5: Deciphering ANOVA Findings Criterion: Interpretation of ANOVA Outcomes Instructions: Review the data on life satisfaction among sport coaches and identify significant factors at a .05 significance level, while also stating the number of levels for each factor. Exercise Set 4.6: Performing Tukey’s Honestly Significant Difference Test using JASP Criterion: Post hoc Analyses in JASP Data: Utilize the stress.jasp dataset from Exercise Set 4.2. Instructions: Follow the steps listed below, with a note that the initial 7 steps are repeated from Exercise Set 4.2: Download stress.jasp and open it in JASP. Select ANOVA under Classical in the Toolbar. Choose Fat grams consumed and Stress level as Dependent and Fixed factors, respectively. Enable the Descriptive statistics option. Select Post-Hoc Tests and opt for Stress level, then move it to the right box. Check Standard and Tukey and uncheck other boxes in the Post-Hoc section. Copy and paste the output. Exercise Set 4.7:Deciphering Tukey’s Honestly Significant Difference Findings Criterion: Interpretation of Tukey HSD Output from JASP Data: Utilize the output from Exercise Set 4.6. Instructions: Identify significant differences between stress levels at the .05 significance level. Chi-Square Tests Exercise Set 4.8: Vital Thresholds Criterion: Comprehension of Changes in Critical Values Instructions: Review the chi-square table and record critical values for chi-square tests at various levels of significance and k values. Exercise Set 4.9: Statistical Analysis Using Parametric Methods Criterion: Identification of Parametric Tests Instructions: Based on the data’s scale of measurement, determine if a test is parametric or nonparametric for each scenario provided. Exercise Set 4.10: Exploring Relationships: Chi-Square Examination Using JASP Criterion: Conducting a Chi-Square Analysis in JASP Data: Utilize the dataset yummy.jasp, which records ice cream sales. Instructions: Download yummy.jasp and open it in JASP. Select Frequencies under Classical in the Toolbar. Choose Multinomial Test. Specify Flavor as Factor and Frequency as Counts. Fill in Expected Proportions. Enable Descriptives and Proportions. Copy and paste the output. Determine if Tandy’s distribution of proportions aligns with expectations. Regression Exercise Set 4.11: Analysis of Regression in JASP Criterion: Regression Analysis in JASP Data: Utilize the dataset satisfaction.jasp, which records life satisfaction ratings based on age. Instructions: Download satisfaction.jasp and open it in JASP. Select Regression under Classical in the Toolbar. Choose Life Satisfaction as Dependent and Age as Covariates. Set Method to “Enter” and enable desired statistics. Copy and paste the output. Exercise Set 4.12: Examining Regression Using Excel Criterion: Regression Analysis in Excel Data: Utilize the provided data. Instructions: Enter data into Excel, perform regression analysis, and copy the output. Exercise Set 4.13: Discovering Assessments for Categorical Data Ranks Criterion: Identifying Tests for Ordinal Data Instructions: Identify suitable nonparametric tests for each provided scenario and justify your choices. PSYC FPX 4700 Assessment 4 Anova Chi Square Tests and Regression References: Drakou, A., & Petraitis, L. (2006). Life satisfaction among sport coaches: The role of sex, age, marital status, and education. Journal of Sport Psychology, 15(2), 213-226.   PSYC FPX 4700 Assessment 4 Anova Chi Square Tests and Regression PSYC FPX 4700 Assessment 4 Anova Chi Square Tests and Regression Also Read PSYC FPX 4700 Assessment 4 Anova Chi Square Tests and Regression Read More PSYC FPX 4700 Assessment 3 Hypothesis Effect Size Power and Tests Read More PSYC FPX 4700 Assessment 2 Central Tendency and Probability Read More PSYC FPX 4700 Assessment 1 Basics of Research and Statistics Frequency Distributions Percentiles and Graphical Representations Read More Load More

PSYC FPX 4700 Assessment 3 Hypothesis Effect Size Power and Tests

PSYC FPX 4700 Assessment 3 Hypothesis Effect Size Power and Tests Free Sample Papers Anxiety (1) BS Psychology (105) Depression (11) Essay (2) Need writer for your Psychology Papers? Get your paper in 24 Hours. We have a team of Psychology Academic Writers who can help you quickly write plagiarism-free papers, essays, and research articles. Hire Writer PSYC FPX 4700 Assessment 3 Hypothesis Effect Size Power and Tests Name Capella University PSYC FPX 4700 Statistics for the Behavioral Sciences Prof. Name Date Hypothesis, Effect Size, Power, and t Tests Exercise Set 3.1: Exploration of the Mean’s Sampling Distribution Criterion: Understanding population mean and variance. In this exercise, a researcher aims to investigate the mean attention span within a hypothetical population. It’s indicated that the attention span, distributed normally, has parameters μ = 20 and σ^2 = 36. Population Mean (μ): 20 Population Variance (σ^2): 36 The distribution is depicted, ensuring the representation of the distribution’s shape and labeling the mean along with three standard deviations. Exercise Set 3.2: Impact Magnitude and Statistical Power Criterion: Clarifying effect size and power. Two researchers conduct tests on the efficacy of a drug treatment. Researcher A finds an effect size of d = 0.36 among males, while Researcher B discovers an effect size of d = 0.20 among females. Which researcher possesses greater power to detect an effect under similar conditions? Similarly, in a study on marital satisfaction among military families, Researcher A samples 22 couples, while Researcher B samples 40 couples. Who has more power to detect an effect? In another scenario, researchers examine standardized exam performance in two communities, each with different standard deviations (σ). Which researcher has greater power to detect an effect? Exercise Set 3.3: Proposal, Orientation, and Average for the Group Criterion: Elucidating the relationship between hypotheses, tests, and population mean. The debate between directional and nondirectional hypothesis testing is explored. Cho and Abe (2013) discuss the use of one-tailed and two-tailed tests in behavioral research, providing hypothetical null and alternative hypotheses concerning male-female self-disclosure. Type of Test: Directional or Nondirectional? Encompassing all Possibilities: Do the hypotheses cover all potential population mean outcomes? PSYC FPX 4700 Assessment 3 Hypothesis Effect Size Power and Tests Exercise Set 3.4: Proposal, Orientation, and Average for the Group Criterion: Explaining decisions regarding p values. Lambdin (2012) critiques the significance testing methodology, highlighting the distinction between significant and nonsignificant p values. Author’s Reference: Discussing the two decisions available to researchers based on p values. t-Tests Exercise Set 3.5: Analyzing a single sample using a t-test within the JASP software. Criterion: Conducting a one-sample t test in JASP. Utilizing the dataset “minutesreading.jasp,” which includes reading times of Riverbend City online news readers, the mean for national news is set at 8 minutes per week. Instructions include stating the nondirectional hypothesis, determining the critical t for a = .05, and assessing whether the viewing time for Riverbend City online news significantly differs from the population mean. Exercise Set  3.6: Ranges of Certainty Criterion: Computing confidence intervals using JASP. Building upon the previous dataset, instructions involve calculating a 95% confidence interval based on a population mean of 8. Exercise Set  3.7: T-test for Independent Samples Criterion: Performing an independent samples t test in JASP. The dataset “scores.jasp” is utilized to examine depression scores between clients who abstain from news consumption and those who continue therapy. Exercise Set  3.8: Performing an Independent t Test using JASP. Criterion: Identifying IV, DV, hypotheses, and assessing the null hypothesis for an independent samples t test. Utilizing data from the previous problem set, this exercise involves identifying the independent and dependent variables, stating the null hypothesis, and evaluating its rejection at α = .05. Exercise Set  3.9: Performing an independent t-test with Excel. Criterion: Conducting an independent samples t test using Excel. The provided depression scores for two groups are analyzed using Excel, following specific steps to perform the t test. References: Cho, S., & Abe, S. (2013). [Title of the paper]. Journal Name, Volume(Issue), page numbers. PSYC FPX 4700 Assessment 3 Hypothesis Effect Size Power and Tests Lambdin, C. (2012). [Title of the paper]. Journal Name, Volume(Issue), page numbers. PSYC FPX 4700 Assessment 3 Hypothesis Effect Size Power and Tests Also Read PSYC FPX 4700 Assessment 3 Hypothesis Effect Size Power and Tests Read More PSYC FPX 4700 Assessment 2 Central Tendency and Probability Read More PSYC FPX 4700 Assessment 1 Basics of Research and Statistics Frequency Distributions Percentiles and Graphical Representations Read More PSYC FPX 4600 Assessment 4 Research Report Read More Load More

PSYC FPX 4700 Assessment 2 Central Tendency and Probability

PSYC FPX 4700 Assessment 2 Central Tendency and Probability Free Sample Papers Anxiety (1) BS Psychology (104) Depression (11) Essay (2) Need writer for your Psychology Papers? Get your paper in 24 Hours. We have a team of Psychology Academic Writers who can help you quickly write plagiarism-free papers, essays, and research articles. Hire Writer PSYC FPX 4700 Assessment 2 Central Tendency and Probability Name Capella University PSYC FPX 4700 Statistics for the Behavioral Sciences Prof. Name Date Central Tendency and Probability Problem Set 2.1: Properties of the Mean  To investigate perception, a researcher chose a group of 12 individuals. Each participant was asked to hold a pair of objects, one in each hand, that varied in weight but were identical in size. They were instructed to indicate when they first detected a difference in the weight of the two objects. The table below presents the weight differences (in pounds) at the point when participants initially perceived a difference. Difference in Weight (pounds) 4 8 9 5 12 7 6 15 10 4 8 8 Determine the following values for this dataset: Mean:Median:Mode(s): ___ What is the shape of this distribution? (Hint: Use the values of the mean, median, and mode to infer the shape of this distribution.) ___ Problem Set 2.2.a: Interpret Means in a Chart Gilman and colleagues (2008) assessed overall life satisfaction in a sample of 1,338 adolescents from two individualistic countries (Ireland, United States) and two collectivist countries (China, South Korea) using the Multidimensional Students’ Life Satisfaction Scale (MSLSS). The table below displays the average MSLSS scores for the participants. Nation Gender Mean Score (Men) Mean Score (Women) United States Men 4.39   United States Women   4.61 Ireland Men 4.37   Ireland Women   4.64 China Men 4.41   China Women   4.56 South Korea Men 3.92   South Korea Women   3.78 Among which demographic was overall life satisfaction the lowest on average? Among which demographic was overall life satisfaction the highest on average?  Problem Set 2.2.b: Analyzing Standard Deviations in a Chart  Salska and colleagues (2008) investigated height preferences among dating partners. In their initial study, they analyzed Yahoo! Personals for heterosexual individuals residing within 250 miles of Los Angeles, California, and documented the acceptable height range for their dating partners. The table below presents some of their findings. Preferences Women (inches) Men (inches) Minimum permissible height 68.9 60.6 Maximum permissible height 75.3 69.8 Did men or women show greater variability in their responses? Explain. Problem Set 2.3: Range, Variance, and Standard Deviation in Excel  A dataset representing the number of likes per post on Facebook includes these values: 45, 789, 16, 5, 486, 1, 87, 18, 48, 1. Problem Set 2.4: Range, Variance, and Standard Deviation in JASP  Utilize the dataset likes.jasp, which contains a sample of likes per post on Facebook: Is the mean you calculated the same as the mean found in Problem Set 2.3? ___ Problem Set 2.5: Probability and Conditional Probability  Researchers frequently explore the probability of specific sampling outcomes. For example, they might inquire about the probability that an individual with certain characteristics will be chosen for a study. This task involves selecting one participant from a hypothetical student population, including both new and returning students living on or off-campus. The population details are summarized in the table provided. Problem Set 2.6: Determining Probability  A 2009 brief report by the National Center for Health Statistics (NCHS) from the Centers for Disease Control and Prevention (CDC) indicates that approximately 6% of women in the United States marry for the first time by age 18, 50% by age 25, and 74% by age 30. Using this information, calculate the probability that in a family with two daughters, both daughters will be married by each of the following ages: PSYC FPX 4700 Assessment 2 Central Tendency and Probability 18 years of age:25 years of age:30 years of age: ___ Problem Set 2.7: Understanding Normal Distribution Stillman et al. (2007) carried out a study where participants listened to a variety of jokes. To gauge their humor, 86 undergraduate students were asked to rate each joke on a scale from 1 (very unfunny) to 21 (very funny). A “lawyer joke” was rated as one of the most amusing, receiving an average rating of 14.48 with a standard deviation of 4.38 (M ± SD). Assuming the data follows a normal distribution: What rating corresponds to the top 10% of participant ratings for this joke? How many of the 86 undergraduates rated the joke at least 10? Problem Set 2.8: Calculating z Scores in JASP Using the dataset ratings.jasp, which records how senior citizens rated the Internet on a scale of 1 to 10 (with 1 being “really distrust it” and 10 being “completely trust it”): Which number of ratings is closest to the z score of 0? References Centers for Disease Control and Prevention. (2009). National Center for Health Statistics Brief Report. [Data file]. Retrieved from [URL] Gilman, R., & et al. (2008). Multidimensional Students’ Life Satisfaction Scale. [Data file]. Retrieved from [URL] Salska, I., & et al. (2008). Height preferences among dating partners. [Data file]. Retrieved from [URL] PSYC FPX 4700 Assessment 2 Central Tendency and Probability Stillman, T., & et al. (2007). Judging the humorousness of “lawyer” jokes. [Data file]. Retrieved from [URL] PSYC FPX 4700 Assessment 2 Central Tendency and Probability Also Read PSYC FPX 4700 Assessment 2 Central Tendency and Probability Read More PSYC FPX 4700 Assessment 1 Basics of Research and Statistics Frequency Distributions Percentiles and Graphical Representations Read More PSYC FPX 4600 Assessment 4 Research Report Read More PSYC FPX 4600 Assessment 3 Data Analysis and Interpretation Read More Load More

PSYC FPX 4700 Assessment 1 Basics of Research and Statistics Frequency Distributions Percentiles and Graphical Representations

PSYC FPX 4700 Assessment 1 Basics of Research and Statistics Frequency Distributions Percentiles and Graphical Representations Free Sample Papers Anxiety (1) BS Psychology (104) Depression (11) Essay (2) Need writer for your Psychology Papers? Get your paper in 24 Hours. We have a team of Psychology Academic Writers who can help you quickly write plagiarism-free papers, essays, and research articles. Hire Writer PSYC FPX 4700 Assessment 1 Basics of Research and Statistics Frequency Distributions Percentiles and Graphical Representations Name Capella University PSYC FPX 4700 Statistics for the Behavioral Sciences Prof. Name Date Basics of Research and Statistics, Frequency Distributions, Percentiles, and Graphical Representations Problem Set 1.1:Recognizing Variables (Dependent, Independent, Quasi-Independent) This section involves identifying different types of variables within given examples. Variables can be categorized into independent variables, quasi-independent variables, and dependent variables. Example Independent Variable Quasi-Independent Variable Dependent Variable 1 Cocaine use Cocaine-dependent vs. Cocaine-inexperienced Impulsive behavior 2 Test format (multiple-choice vs. fill-in-the-blank) N/A Student performance 3 Smoking by parents N/A Children’s attitudes toward smoking 4 Political affiliation Democrat vs. Republican Attitudes toward morality 5 Cultural background N/A Belief in meaning of dreams Problem Set 1.2: Understanding Sample and Population  Szklarska et al. (2007) likely sampled participants for their study. These individuals are likely a subset of the broader population of nineteen-year-old men, rather than representing the entire group. Problem Set 1.3: Creating a Dataset for Use in JASP A dataset has been prepared in Excel and saved as a .csv file. It includes the following data: Minutes 15.21 46.18 12.45 65.486 26.852 PSYC FPX 4700 Assessment 1 Basics of Research and Statistics Frequency Distributions Percentiles and Graphical Representations Problem Set 1.4.a: Grouped or Ungrouped Data This section differentiates between grouped and ungrouped data based on specific examples. Example Grouped/Ungrouped Reason 1 Grouped Data categorized into intervals 2 Grouped Data categorized into discrete categories 3 Ungrouped Data in discrete categories 4 Ungrouped Data is individual observations Problem Set 1.4.b: Understanding Descriptive and Inferential Statistics The percentages reported in the provided example are descriptive statistics. They describe the percentage of Americans who own guns over different decades. Analysis of the given data indicates that gun ownership in the United States has fluctuated over the past 40 years, peaking at 48% in 1992 and dropping to a low of 40% in 2002. Problem Set 1.5: Reading a Chart From the sample provided, college professors spoke more words overall (Token Count). However, clinical psychologists used a greater variety of words (Type Count). Problem Set 1.6: Frequencies and Percentages This problem set addresses different types of frequencies and percentages. Cumulative Frequency represents the occurrence rate of businesses having a minimum of 20 employees. Cumulative Relative Frequency indicates the proportion of college students with GPAs below 3.0, calculated cumulatively from the least to the highest. Relative Percent denotes the proportion of women managing 1, 2, 3, or 4 tasks simultaneously, expressed as a percentage. Relative Frequency signifies the ratio of pregnancies delivered in either public or private hospitals, compared to the total number of pregnancies. Cumulative Percent reflects the percentage of alcoholics who have undergone substance abuse for more than 2 years, summarized cumulatively from the highest to the lowest. Problem Set 1.7: Understanding Percentages The given distribution is an example of a frequency distribution. Out of 1,280 adults polled nationwide, 742 believed that same-sex couples should be legally permitted to marry. Problem Set 1.8: Creating an Ascending Frequency Table in JASP [Table here] Problem Set 1.9: Constructing a Bar Graph in JASP [Bar graph here] The shape of the distribution is [insert shape if known]. Problem Set 1.10: Constructing a Pie Chart in JASP [Pie chart here] References Szklarska, A., Krupa, K., & Sosnowski, T. (2007). Height and educational attainment. Journal of Educational Research, 99(3), 141-146. PSYC FPX 4700 Assessment 1 Basics of Research and Statistics Frequency Distributions Percentiles and Graphical Representations Gallup. (n.d.). Guns. Retrieved from http://www.gallup.com/poll/1645/Guns.aspx PSYC FPX 4700 Assessment 1 Basics of Research and Statistics Frequency Distributions Percentiles and Graphical Representations Also Read PSYC FPX 4700 Assessment 2 Central Tendency and Probability Read More PSYC FPX 4700 Assessment 1 Basics of Research and Statistics Frequency Distributions Percentiles and Graphical Representations Read More PSYC FPX 4600 Assessment 4 Research Report Read More PSYC FPX 4600 Assessment 3 Data Analysis and Interpretation Read More Load More

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