- Present the key descriptive statistics for the five quantitative variables in a table (quantity sold, advertising expenses, flavor rating, social media posts, and event promotions). The key descriptive statistics include the mean, median, standard deviation, and range.
- Analyze the TC Ice Cream data to identify trends and patterns for the two flavors you have selected. For each flavor, create the following visualizations.
- Create a line chart (also known as a trend chart) using the qualitative variable Date and the quantitative variable Quantity Sold to provide a visualization displaying quantity sold by month.
- Create a line chart (also known as a trend chart) using the qualitative variable Date and the quantitative variable Flavor Rating (average) to provide a visualization displaying flavor rating (average) by year/quarter/month.
- Create a combo chart using the qualitative variable Date (x-axis) and the quantitative variables: Quantity Sold (clustered column) and Advertising expenditures (line – secondary axis).
- Create a combo chart using the qualitative variable Date (x-axis) and the quantitative variables: Quantity Sold (clustered column) and total – Social Medial Posts and Event Promotions (line – secondary axis). Hint: create a pivot table variable to sum the social media posts and event promotions.
- Create a box and whiskers chart using the qualitative variable Quantity Sold. This will help identify any outliers in the quantity sold data.
- Create a histogram for the quantitative variable Flavor Rating. It is recommended to use the data analysis “add-in” and the analysis tool “Histogram” to create the data for the visualization.
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Tag: variable
A risk factor is a variable associated with an increased risk of disease, mental health challenges, academic delays, developmental delays, poor relationships or boundary-setting, etc.
This should address a specific risk factor, clearly explain why it is a risk factor, and offer quick guidance on how to combat it/overcome it, move the needle forward to decrease the risk, or where to go for support and resources. Think of empowering them with information and actionable steps!
● You will have the option to be creative by creating an awareness campaign via:
○ An ad that can go on buses, freeway signs, benches ○ A Tik-Tok video or set of Instagram slides ○ A YouTube or facebook video where you share PowerPoint slides
or get creative with how you visually demonstrate the material (don’t just record yourself talking).
○ An interactive webpage or PDF (with working links) ● If you have the consent of others, they may also appear in your campaign but
you have to do the work of coming up with the content, script, editing, etc. ● In true form, campaigns are meant to be disseminated widely, captivating so
that they get your message across quickly, easily shareable and accessible. ● This is a useful exercise because social media and technology play an
important role in reaching parents and children/adolescents – especially now that COVID-19 has pushed the need for virtual communication and has increased isolation for many.
In a document include:
1. Target population. Be Specific! ○ What group of parents are you targeting? Some things to
consider: ○ The age of their children. Do you want to
target parents with teens, infants, middle schoolers, etc
○ The geographic area that they live in. Do you want to target parents who live in an area with high levels of air pollution or pesticides? Or parents with little access to non-processed foods?
○ The social climate and context. Are you targeting parents in a school district with depleting funds/resources? Or parents whose
kids may be experiencing heightened levels of discrimination due to socio-political discourse?
○ Physical (dis)abilities. Do you want to reach parents of children with a specific physical need or health challenge (e.g., hard of hearing, blind, wheelchair-bound)?
○ Health issues. Do you want to reach parents with a specific health issue (e.g., diabetes, asthma, cancer)?
○ Family structure. Do you want to target separated/divorced co-parenting parents? Or military families who travel often or go long periods without seeing one parent? Incarcerated parents or the parent who is not incarcerated but whose partner is? Parents living in multigenerational homes?
○ Other ideas: Recent immigrant parents who are not fluent in English? Young teen parents, who have been kicked out? Parents in college?
2. The risk factor your campaign is addressing. Be Specific, go beyond saying poverty!
○ For example: ○ Having low access to libraries, educational
materials for the home, or to enrichment activities outside the home
○ Living in food deserts or living near freeways or factories
○ Social isolation or poor relational (community, school, or family) support
○ Decreased access to mental health services or academic counseling
3. What does this risk factor increase the chances of? Be thorough and detailed in explaining how/why it increases the risk of certain outcomes.
○ The risk of falling behind academically (e.g., the number of vocabulary words a child knows – example: NYC Read The City)
○ The risk of health-related challenges (e.g., malnutrition, asthma)
○ The risk of drug use, early sexual activity, gang membership, increased displays of anger or frustration, etc
○ The risk of heightened anxiety, depression, poor or lacking goal setting, poor daily routines, etc
4. How can parents positively intervene, make social or environmental changes, adjust home life or communication approaches, be advocates for their children, locate and access resources, etc to remove the risk factor or create buffers to decrease the chances of the risk factor from leading to negative outcomes or experiences.
○ Empower them! ○ Avoid placing blame on the parents and avoid using
deficit-based language ○ Provide specific actionable steps
5. What strategy would you use to disseminate the campaign and raise awareness?
○ What organizations would you partner with if any? Why or why not?
○ What media outlets, platforms, or physical spaces would you use to showcase the campaign material? Why?
○ How long would the campaign run for? Are you choosing to run it in a particular month, week, or season? Why?
6. References ○ Minimum of 3 citations in APA format at the end ○ Also…use in-text citations in the word doc but no need to
include them in your actual awareness campaign material
○ Your references can be peer-reviewed journal articles, policy briefs, or brief reports
* Attach your actual campaign material either as an embedded link within the document, an image posted at the end of the document, or as a separate document. Whichever works best for your content.
*Your visual should be clear and captivating. You do not need to have everything you write out in the document above written or displayed in your actual visual. However, your campaign material should truly be in alignment with what you described in the document. Think about what your message is and what you want to promote and avoid highlighting what you don’t want parents to do or say (instead focus on what they can do or say to buffer against the risk factor being addressed)
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Details: Variable Questions and Data Privacy
Variables must vary
Variables are essential part of quantitative research, thus understanding fundamental articulation on variables such as different types of variables, operationalization and measurement and, scales of variables underpin in an effective platform for variables comprehension. In particularly, “variables must vary” posit a significant implications in variables understanding , accommodating fundamental variability features in a quantitative research and comprehension of variables as essential part in a quantitative research. This statement (“variables must vary.”) implies that different units, or participants in a must indicate differences in the variable. For example in one study, gender may be variable demonstrating difference unit or participant. Significantly, one study, focusing on married women will great gender as a non-variable in a study, while married women form a significant variable for the study. Therefore, the statements (“variables must vary.”) are fundamental, demonstrating that different units and participants must indicate different variable in a research study.
Levels of variables measurement
Significantly, understanding the operationalization and measurement of variables are essential strategies for effective data quantification and decision-making in a research study. Scales of variables measurement is fundamental because it provide effective articulation on the relationship between variables and conclusion in a research study for practical implications and conclusion. In a comprehensive understanding of the variables, there are four different level of variables measurement that requires effective articulation and description to effectively operationalize and measure variables in a consistent and accurate manner in a research study. Notably, variable measurement levels including nominal measurement, ordinal level, interval and ratio variables. Nominal level of variable measurement describes one fundamental basic measure that contains two or more mutually inclusive and exclusive categories that cannot be ordered. For instance, a list of states in India Himachal Pradesh, Uttaranchal, Maharashtra are nominal variables that require specific rile for effective ordering and ranking. Accommodating rules such as alphabetical order would provide an effective platform for data ordering and ranking States in India in alphabetical order. Similarly, gender, accommodating male, female and third gender is vital examples of nominal variables measurement.
Consequently, ordinal variable describes level of variable measurements in which two or more categories like in nominal measurement of variables. However, ordinal variable can be ranked, accommodating the ranking capabilities in differentiating categories in such variables. Noteworthy, ranking in ordinal variables measurements level do not contain numerical value; hence can only be measure in terms of greater or lesser than. For example asking a student who often they read in day would provide significant example of ordinal variables measurement levels. For instance, frequently, sometimes, yes or no are vital examples of ordinal measurement of variables. Interval is vital level of data measurements that accommodates significant articulation on numerical value and continuum measurement that requires effective articulation. Specifically, Interval variables are variables that have a numerical value, and are measured on a continuum, accommodating equal interval between values and items. For instance a temperature measured in Celsius or Fahrenheit is a vital example of interval level of variable measurements. For instance, the difference between 20 degrees Celsius and 30 degrees Celsius is equal to the different between 30 degrees Celsius and 40 degrees Celsius. Similarly, the example, 1 dollar to 2 dollars is the same interval as 88 dollars to 89 dollars gives another significant example in interval level of variable measurements. Finally, the ratio variables measures numerical value and continuum, however the ratio values are in absolute zero. This zero on the measurements scale indicating no value of the variable or the unit or items measured is absent at level zero. Some significant examples of ratio variables level of measurement include height, weight, currency, mass, among others. Thus, scales of measurement of variables are nominal, ordinal, interval and ratio, accommodating categories, numerical value, and order among other issues in variables instances of variable measurement level.
Discreet and Continuous Variables
Understanding data accommodates quantitative and qualitative data in a study. In statistical analysis, accommodate quantitative data provide significant attention to discrete and continuous variables that posits fundamental characteristics. Discrete variables are variable assuming a finite number of isolated values. In contrast, Continuous variables define variables that assume infinite number of different values. According to the author, understanding discrete and continuous variables accommodates meaning, specific numbers range, classification, assumption and representation (Allen 2017). On one hand, discrete variables constitute complete range of numbers, while continuous variable define an incomplete rage of number. Similarly, discrete variables obtains value through counting while, continuous variable obtain values through measuring. Discrete variables assume distinct or separate values. In contrast continuous variables assume any value between the two values. Finally, in classification, discrete variables describe non-overlapping classification, while continuous variables identify overlapping classifications. For example, the discrete variable is describable with possible values such as 1, 2, 3… while continuous variable can define how far a ball thrown upwards will take to settle, accommodate measurement accuracy for actual value determination. Thus, understanding the comparison between discrete and continuous variables provide a vital platform for decision-making in data usage and operationalization.
In calculation, discrete variables are insignificant information that gives less accurate outcomes for decision-making and process improvement. Accommodating accuracy in using discrete variables requires repeated measurements (Berkman, & Reise, 2012) Therefore, dependability on probability of the actual magnitude depends on the accuracy of the values.
Level of measurement for:
Career field (e.g., accountant, production manager,). This is Nominal level of variable measurement because it describes one fundamental basic measure that contains two or more mutually inclusive and exclusive categories that cannot be ordered.
Temperature in Fahrenheit. This is Interval variables measurement of variables because there are variables that have a numerical value, and are measured on a continuum, accommodating equal interval between values and items.
A job satisfaction survey measured as “disagree, neutral, agree” is an example of ordinal variable describes level of variable measurements because there are two or more categories like in nominal measurement of variables.
Finally, an example, Total sales for a firm is an example of, the ratio variables because it measures numerical value and continuum; however the ratio values are in absolute zero.
Types of a variable
The number of workers in each department of a large organization describes discrete variable because these are variables are variable assuming a finite number of isolated values.
The dollars of revenue earned during a fiscal year is discrete variable accommodating variables have variable assuming a finite number of isolated values.
The number of software licenses available to employees in a firm is an example of discrete variables because, variables have variable assuming a finite number of isolated values
Finally, the average annual salary of middle managers of an organization demonstrates continuous variable because the variables that assume infinite number of different values
Data Privacy
Data privacy is a fundamental concern for business organization and researchers that require pragmatic articulation to ensure availability, integrity and confidentiality of data. Specifically, creating a significant platform for effective data collection, processing, analysis and transmission, security privacy is a vital consideration in data management. In a research scenario, accommodating techniques such as information security practices and data privacy and confidential through a robust data protection strategies such as access control , authentication and data transmission and sharing polices provide an enhanced platform for data privacy. Notably, organizations dealing with customers’ data for decision-making require a robust platform for a secure data protection platform. Specifically, embracing data privacy principles including fair, lawful and transparency, accuracy, storage limitation, integrity and confidentiality and accountability are vital for effective data privacy concepts (Medine, and Murthy, 2020). Therefore, Data privacy is a vital concern that requires real-time solution and technology-based strategies for a secure and safety data management systems.
References
Allen, M. (2017). Variables, Continuous. In: The SAGE Encyclopedia of Communication and Research methods. SAGE Publications
Berkman, E.T., & Reise, S.P. (2012). A Conceptual Guide to Statistics Using SPSS. Thousand Oaks, California, United States: SAGE Publications, Inc.
Medine, D., and Murthy, D. (2020). New Approaches to Data Protection and Privacy. https://www.cgap.org/sites/default/files/publications/2020_01_Focus_Note_Making_Data_Work_for_Po
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Many business activities generate data that can be thought of as random. An example described in the textbook is the servicing of cars at an oil change shop. Each car entering the shop can be considered an experiment with random outcomes. A variable of interest in this experiment could be the amount of time necessary to service the car. Service time will vary randomly with each car.
We can often capture the most relevant characteristics of a stochastic process with a simple probability distribution model. We can then analyze the model to make predictions and drive decisions. For instance, we could estimate the number of technicians the oil change shop needs to service demand on a Saturday afternoon. Discuss the following:
- What is a random variable?
- How would you differentiate a discrete from a continuous random variable?
A laptop manufacturing company has implemented a 2-step process to test the quality of each production batch. In the first step, a technician randomly selects 15 laptops from the batch and determines whether they meet specifications. The batch is considered acceptable provided no more than 1 laptop fails to meet specifications. Otherwise, the entire batch must be tested in the second step. Historical data shows that 95% of the laptops produced adhere to specifications. Discuss the following:
- What are the 4 characteristics of a binomial experiment?
- Can we use a binomial distribution to model this process?
- What is the probability that the entire batch unnecessarily has to be tested if in fact 95% of its laptops conform to specifications? (Hint: Use Excel’s =BINOMDIST() function to find the probability.)
- What is the probability that the batch is incorrectly accepted if only 75% of its laptops conform to specifications?
Due Day 7
Reply and or respond to at least 2 of your classmates or your faculty member, and/or address the following subjects:
- Explain what we mean when we identify “cause and effect”.
- How are percentages an important part of determining probability?
- Why do we use “degrees of freedom?”
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- How would you differentiate a discrete from a continuous random variable?
In this homework assignment you will use census data from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau. A copy of this dataset is located at UCI Machine Learning re
Need help with Python programming
In this homework assignment you will use census data from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau. A copy of this dataset is located at UCI Machine Learning repository, please see this link to reach to the dataset website. This dataset contains census data extracted from the 1994 and 1995 Current Population Surveys. We will only work with ‘training’ data (a link to that is provided to you below). The data contains 41 demographic and employment related variables. The abbreviated column names provided to you below. You are expected to read the documentation of this dataset, understand the features and preprocess this dataset. Additional information can be found in the data description and additional comments. Below you will find a code snippet to download and read the data into a pandas dataframe. You can alternatively download it yourself, extract and read it manually. The questions are shown in the subsequent cells. You can provide your answers in this file. Make sure to change the notebook’s name and add your name before submitting.
### Q1 – Identify the data scales and data types for each variable in census data. Identify the domain for each variable by checking the attributes’ values. Then, create a data quality report for both categorical (nominal, ordinal) and continuous (interval, ratio) variables. For data scales, identify whether an attribute is nominal, ordinal, interval or ratio scale. For data types, identify the domain and provide an appropriate data type (integer, float, String, date, Boolean). See if that data type is correct in your dataframe. For domain, inspect each distinct value for each attribute. Identify missing values. Also include the bar plots and histograms for visualizing the distributions. The examples for a continious and a categorical feature can be seen below. You do not need to use jupyter formatting provided here. You can print a DataFrame or read a csv, and display it. Make sure you have the csv in your zip file.
Q2 – Identify the data quality issues for each attribute. Create a data quality plan and implement the changes. Identify missing values, potential anomalies and outliers. Finally, remedy these issues.
Q3 – For all the interval and ratio scale features, create a scatter plot matrix (pairplots) and correlation matrix. For all ordinal scale features, create a correlation matrix using Spearman correlation. Use the data scales list you created in when creating a correlation matrix using Spearman rank, please use all features having an order (i.e., ordinal, interval, ratio scale variables) and not just ordinal features.
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MANAGERIAL ACCOUNTING
Assessment Weight: 50 total marks
Instructions:
• All questions must be answered by using the answer boxes provided in this paper.
• Completed answers must be submitted to Blackboard by the published due date and time.
Submission instructions are at the end of this paper.
Purpose:
This assessment consists of six (6) questions and is designed to assess your level of knowledge of the key topics covered in this unit
Assessment Design – Adapted Harvard Referencing
Holmes has been implementing as a pilot program using a revised/adapted Harvard approach to referencing. The following guidelines apply:
• Reference sources in assignments are limited to sources which provide full text access to the source’s content for lecturers and markers.
• The Reference list should be located on a separate page at the end of the essay and titled: References.
• It should include the details of all the in-text citations, arranged alphabetically A-Z by author surname. In addition, it MUST include a hyperlink to the full text of the cited reference source.
For example;
P Hawking, B McCarthy, A Stein (2004), Second Wave ERP Education, Journal of Information Systems Education, Fall, http://jise.org/Volume15/n3/JISEv15n3p327.pdf
• All assignments will require additional in-text reference details, which will consist of the surname of the author/authors or name of the authoring body, year of publication, page number of content, paragraph where the content can be found.
For example;
“The company decided to implement a enterprise wide data warehouse business intelligence strategies (Hawking et al, 2004, p3(4)).”
Non-Adherence to Referencing Guidelines
Where students do not follow the above guidelines:
- Students who submit assignments which do not comply with the referencing guidelines will receive a 10% penalty.
- Students who submit assignments in which the citations are “fake” will be reported for academic misconduct.
Question 1 (7 marks)
Part A
Asco Company has a relevant range of production between 15,000 and 30,000 units. The following cost data represents average variable costs per unit for 25,000 units of production.
Required:
a) If 25,000 units are produced, what is the variable cost per unit? (1 mark)
b) If 16,000 units are produced, what is the variable cost per unit? (0.5 mark)
c) Comment briefly on your answers to (a) and (b). (1 mark)
d) If 18,000 units are produced, what are the total variable costs? (1 mark)
Part B
GEM Ltd leases a photocopy machine with terms that include a fixed fee each month plus a charge for each photocopy made. GEM made 5,000 copies and paid a total of $600 in January. In April, they paid $400 for 3,000 copies.
Required:
a) What is the variable cost per copy if GEM uses the high-low method to analyze costs? (1.5 marks)
b) How much would GEM Ltd pay if it made 7,500 copies? (Hint: Need to solve for Fixed cost) (2 marks)
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Question 2 (11 marks)
Henry’s Kitchens makes two types of sandwich makers: Basic and Deluxe. The company expects to manufacture 70,000 units of Basic, which has a per-unit direct material cost of $10 and a per-unit direct labor cost of $60. It also expects to manufacture 30,000 units of Deluxe, which has a per-unit material cost of $15 and a per-unit direct labor cost of $40. It is estimated that Basic will use 140,000 machine hours and Deluxe will require 60,000 machine hours. Historically, the company has used the traditional overhead allocation method and applied overhead at a rate of $21 per machine hour. It was determined that there were three cost pools, and the overhead for each cost pool is shown:
Machine setups $ 90 000
Machine processing 4 000 000
Material requisitions 100 000
Total overhead $ 4 190 000
The cost driver for each cost pool and its expected activity is shown:
Basic Deluxe Total
Machine setups 100 200 300
Machine hours 140 000 60 000 200 000
Parts requisitions 80 120 200
Required:
a) What is the per-unit cost for each product under the traditional overhead allocation method? (3 marks)
b) What is the per-unit cost for each product under ABC costing? (4 marks)
c) Briefly comment on the overhead applied per unit under the two overhead allocation methods. i.e. How much was overhead under or overapplied for each product? Further, would you recommend a change to ABC costing for Henry’s Kitchens? Why or why not? (4 marks)
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Question 3 (7 marks)
Relevant data from Picta Company’s operating budgets are presented below. The company’s financial year ends on 30 June.
Quarter 1 Quarter 2
Sales $248,470 $251,539
Direct material purchases 120,295 128,832
Direct labor 76,553 74,289
Manufacturing overhead 26,000 24,400
Selling and administration expenses 33,500 33,500
Depreciation included in selling and administration expenses
2,000
2,500
Collection from customers 230,524 220,116
Cash payments for purchases 114,345 118,346
Additional data:
Equipment was sold in July for $8,000 and $4,500 in November. Dividends of $5,500 were paid in August. The beginning cash balance was $80,395 and a required minimum cash balance per quarter is $60,000.
The company has a 15% open line of credit for $70 000 with their bank.
Required:
a) Use this information to prepare a cash budget for the first two quarters of the year. (5 marks)
bi) Briefly comment on Picta Company’s expected cashflow position in the first two quarters of the year. (2 marks)
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Question 4 (7 marks)
The income statement for Forklift Electrical Ltd for two years are shown below:
Required:
a) Determine the operating income (loss) (dollars) for each year. (1 mark)
b) The company made a strategic decision to invest in additional assets in the current year. These
amounts are provided. Using the amounts of the total assets as the investment base, calculate the return on investment. (1 mark)
c) Was the decision to invest additional assets in the company successful? Explain. (1 mark)
d) Assuming an 8% cost of capital, calculate the residual income for each year. (2 marks)
e) Would the management of Forklift Electrical Ltd have been more likely to accept the investment opportunity if the residual income had been used as a performance measure instead of ROI? Explain your answer. (2 marks)
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Question 5 (11 marks)
Micol & Co. Ltd sells a single product, baby hamper, with a selling price of $150 and variable costs per baby hamper of $100. The company’s monthly fixed expenses are $200,000.
Required:
a) What is the company’s break-even point in units? (2 marks)
b) What is the company’s margin of safety in dollars, assume sales is expected to be $800,000? (2 marks)
c) How many baby hampers will Micol & Co. Ltd need to sell (in sales dollars) in order to realize a target profit of $500,000? (2 marks)
d) Construct a contribution margin income statement for the first month (in July) that reflects $2,400,000 in sales revenue for Micol & Co. Ltd. (3 marks)
e) Provide two suggestions to Micol & Co. Ltd on how it can increase profit in subsequent months? (2 marks)
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Question 6 (7 marks)
Technology Inc. Ltd sells desktop computer printers for $65 per unit. Unit product costs are:
A special order to purchase 10,000 desktop computer printers has recently been received from another company, and Technology Inc. has the idle capacity to fill the order. The company will incur an additional $1.50 per printer for additional labor costs due to a slight modification the buyer wants to be made to the original product. One-third of the manufacturing overhead costs are fixed and will be incurred no matter how many units are produced. $2,100 of existing fixed administrative costs will be allocated to the order as “part of the cost of doing business”.
Required:
a) Which of the data above should be ignored in making the special-order decision? For what reason? (2 marks)
b) Should Technology Inc. Ltd accept the order if the buyer offers $38 per unit for 10,000 desktop computer printers? (3 marks)
c) What factors must any company consider before accepting a special-order contract? (2 marks)
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END OF FINAL ASSESSMENT
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• Only one submission is accepted. Please ensure your submission is the correct document.
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The Excel file for this assignment contains a database with information about the tax assessment value assigned to medical office buildings in a city. The following is a list of the variables in the database:
- FloorArea: square feet of floor space
- Offices: number of offices in the building
- Entrances: number of customer entrances
- Age: age of the building (years)
- AssessedValue: tax assessment value (thousands of dollars)
Use the data to construct a model that predicts the tax assessment value assigned to medical office buildings with specific characteristics.
- Construct a scatter plot in Excel with FloorArea as the independent variable and AssessmentValue as the dependent variable. Insert the bivariate linear regression equation and r^2 in your graph. Do you observe a linear relationship between the 2 variables?
- Use Excel’s Analysis ToolPak to conduct a regression analysis of FloorArea and AssessmentValue. Is FloorArea a significant predictor of AssessmentValue?
- Construct a scatter plot in Excel with Age as the independent variable and AssessmentValue as the dependent variable. Insert the bivariate linear regression equation and r^2 in your graph. Do you observe a linear relationship between the 2 variables?
- Use Excel’s Analysis ToolPak to conduct a regression analysis of Age and Assessment Value. Is Age a significant predictor of AssessmentValue?
Construct a multiple regression model.
- Use Excel’s Analysis ToolPak to conduct a regression analysis with AssessmentValue as the dependent variable and FloorArea, Offices, Entrances, and Age as independent variables. What is the overall fit r^2? What is the adjusted r^2?
- Which predictors are considered significant if we work with α=0.05? Which predictors can be eliminated?
- What is the final model if we only use FloorArea and Offices as predictors?
- Suppose our final model is:
- AssessedValue = 115.9 + 0.26 x FloorArea + 78.34 x Offices
- What wouldbe the assessed value of a medical office building with a floor area of 3500 sq. ft., 2 offices, that was built 15 years ago? Is this assessed value consistent with what appears in the database?
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- Create a title page that includes your student number.
- Use gretl to generate 1,000 observations from the uniform distribution that ranges from 0 to 45 and name the variable U1.
- Use gretl to generate another 1,000 observations from the uniform distribution that ranges from 0 to 45 and name the variable U2.
- Create a new variable S2 that is equal to the mean of U1 and U2. This variable contains 1,000 samples of the mean of two uniform variables. Now, you have 1,000 samples of the mean of two uniform variables. [Tip: To create a new variable such as S2 right-click in gretl, select ‘Define new variable’ and type S2 = (U1 + U2)/2]
- Make a histogram for S2. Include a copy of the histogram in your assignment with a properly labelled x- and y-axis. Describe the distribution in two or three sentences. Be sure to comment on the shape, center and spread. Incorporate statistics whenever appropriate.
- Use gretl to generate 1,000 observations from the uniform distribution that ranges from 0 to 45 ten more times and name the variables U3 through U12.
- Create a new variable S12 that is equal to the mean of U1 through U12. Now, you have 1,000 samples of the mean of twelve uniform variables.
- Make a histogram of S12. Include a copy of the histogram in your assignment with a properly labelled x- and y-axis. Describe the distribution in two or three sentences. Be sure to describe the shape, center and spread. Incorporate statistics whenever appropriate.
- In general, explain the effect of increasing the sample size from 2 to 12 using the results you have found in this assignment. Be sure to comment on the shape, center and spread. Incorporate statistics whenever appropriate.
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Make sure you have thoroughly read and reviewed the Chapter 2 text and powerpoint.
Instructions
Part 1: Initial Post
Write one paragraph of 5-7 sentences on each of the three topics below. This is a total of three paragraphs. You should use this three paragraph format for all discussion boards.
- Define (in your own words) the following terms: experimental group, control group, independent variable, and dependent variable.
- True random sampling can be difficult to obtain. Explain the following concepts: population, random sample, representative group, random assignment. Explore the idea of using the popular convenient sample of students enrolled in an Introduction to Psychology course. What are the advantages and disadvantages of this type of sample?
- Propose a simple approach to studying a psychological issue you are interested in. Make sure to include the independent variable, dependent variable, and sample.
Part 2:
1.Which two early fields led to the formation of the field of psychology? After identifying those two fields, describe the study of each field and give a real-world example of something that could be studied by each of the two.
2.Explain the two first theories of psychology (structuralism and functionalism). Be sure to include the focus of study and the methods of each theory.
3.Explain the theory of behaviorism. How was behaviorism different from previous psychological theories? What were the behaviorists studying and how did they study it? Give a real-world example of something that could be understood using behaviorist theory.
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