ASSIGNMENT SOLUTION
Question Details……………..
THE FLINDERS UNIVERSITY OF SOUTH AUSTRALIA
College of Science & Engineering
STAT8721 Data Science Major Assignment 2. 30%
Please submit your written reports, and presentation slides through FLO by 5pm Friday 13th June.
You are required to present your research in the final week of semester. You will be assigned a time and all group members must attend and present.
Requirements
• Demonstrate an understanding of good data science practice.
• Conduct data analysis to identify and test potential hypotheses.
• Present the results of data analysis in written, graphical and verbal forms.
• Develop and demonstrate your presentation skills.
The aim of this assignment is to encourage you to conduct evidence based research, critique such evidence and present scientific results in a range of standardised forms.
You will work in the same group as you did for assignment 1.
Assignment scenario
I am a supermarket manager wanting to improve business performance and profits. I have several data sets that have been used for previous data analysis. I have provided all available data sets for you to use but you will need to combine them. I am interested to know more about one area of business operation. Based upon your group number, you are asked to focus on and present a report that will provide evidence upon which my board members and I can base our business decisions in response to one of the following questions.
Student 3 . How I can sell more products?
Task 1 – Create a data set and develop a hypothesis (10 marks) (Group).
1. Download and combine all supermarket data sources from FLO. Submit as a single data file.
2. Report on issues in linking and combining data. What problems were presented and how did you overcome them? How much data did you exclude and how much is available to use? What is the potential impact of the data loss?
3. Run data mining association rule analysis on your combined data set to find patterns that can form hypotheses. Discuss the patterns found and select one pattern to analyse further. Rewrite the
pattern as a hypothesis. Explain and justify your selection for hypothesis. Note that a null hypothesis is not valid in this assignment.
Task 2 – Test your hypothesis and report findings (group).
1. Develop and appropriately present summary statistics, and any other methods you need, to suggest if the hypothesis should be accepted or rejected. Justify all methods and discuss all results in the context of the hypothesis. Make a clear statement regarding support for the hypothesis.
Task 3 – Present findings to the board (group).
1. Write a 3 page executive summary for the ‘client’ on what you did (your methodology) and your findings. This should present the outcomes of the work completed in task 2. Provide a clear statement regarding how the business should/could use or apply your findings. Align your report to the business focus area and your hypothesis. (15 marks).
2. To support your report you are required to present your findings as a company board presentation in the final week of semester. Each presentation should be no more than 7 minutes and follow a power point presentation of no more than 5 slides. (15 marks).
3. Each group will present to the class members and guests and convince them of the value of the analysis and findings. (10 marks)
Task 4 – Individual analysis and Assessment
1. Explain how, if you had more time, you would extend the research you have conducted. What were the key issues encountered by your group and how would you overcome/manage these issues in future work? Provide a short discussion of the work you contributed to the group report. What do you feel you as an individual did well and where do you feel you could improve? (10 marks)
Submission
As a group you must submit the following files to FLO by the deadline.
1. A single file containing the combined data set used for analysis.
2. A single, PDF file listing all group members and reporting on the activities and outcomes for task 1 and your executive summary resulting from task 3 separated by a business appropriate title page. Maximum of 3 pages for each part excluding title pages. (Only listed group members will receive a grade.)
4. A single power point file containing the slides for your board presentation.
NOTE: Each group will present in the final week of semester and use this to gain feedback to revise their final submissions.
As an individual you must each submit a single PDF file containing your individual analysis of no more than 2 pages.
DETAILED EXPLANATION OF ASSIGNMENT
THE FLINDERS UNIVERSITY OF SOUTH AUSTRALIA
College of Science & Engineering
STAT8721 Data Science Major Assignment 2. 30%
Course Name-
Teacher Name-
Your Name-
Date-
Abstract
Hypothesis data is information that can be counted or displayed as a number. Due to the amount of digital data it can be used in calculating and statistical testing. These are also the data that are visible in tables and graphs. Order data can be classified as dashed or broken. Quality data is continued as the volume data has been dropped. Quality data is a description that explains the type of question using the word instead of the number that generates the mood or digital data output texture. “The research is described as having quantitative or qualitative data related to using facts, accusations and variables.” In fact, the claims and variables that are represented by numbers are considered quantitative information. The form or type form is regarded as quality information. In most scientific studies, information and quantitative features have been demonstrated and analyzed ”
Task 1 – Create a data set and develop a hypothesis (10 marks) (Group).
Overall Framework
Research data is data that is monitored, monitored, or digitized for analysis to obtain the results of the original research. According to Cooper and Schindler (2014), “Secondary data has at least translations between its events and its records.” Vitality is seeking their closeness with truth and error checking. The procedure for collecting data and gathering the results. “Quantitative data is information that can be counted or numerical display. Because the amount of digital data that can be used in the calculations and statistical tests. These are the data that has been seen in tables and graphs. The sequence data can be categorized as dashes or continuous quality data. Still persists when data volumes are dropping.
Qualitative
Qualitative research, including data analysis, such as a picture or object. Data quality is often used to identify problems or generate new ideas for research or intervention, it may be useful to add volume to the Assessment program. Advantageous goal is to understand the importance of Testing people’s culture and specific issues or cases, known as a case study. The study is used to demonstrate quality and understand the ideas and views of the grounds for the decision.
Task 2 – Test your hypothesis and report findings (group).
The quality of interpretation and translation studies to collect data while observing what people say or do. When comparing the two methods of investigation Quality Papers are more subjective than quantitative research. Quality research uses different approaches to collecting data or information such as in-depth interviews with individuals and groups. The main reason for this type of research approach is openness and exploration. Usually there is a small group that focuses on the interview. Participants are asked to answer the general questions and interviewees or group coordinators and find out their answers to identify and define the thoughts and feelings of people about the topic or ideas under discussion and determine the level of agreement within the group. Qualitative research is more and more required, and requires researchers to interpret data to implement subordinate thoughts, often including interviews with open, specific questions about the status and observations. For example, researchers want to know if a youth program can help teenagers who are struggling. Researchers will talk to the participants and ask, “What do you think about the youth program?” Then the researchers will interpret the results. Quality is subject, interpretation and description. “Qualitative research is suitable for the purpose of description, interpretation and explanation” (Imel, Kerka & Wonacott, 2002).
According to Nieswiadomy (2008) statistics can be classified into two variants, descriptions and combinations. Statistical descriptions pertains to organizations and digital data collection models or populations. There are 4 types of description statistics: 1) data concentration gauge 2) middle trend measures 3) volatility measures and 4) communication measures. Statistics refer to “assumptions” that can be made for the population of sample data. Description descriptors allow investigators to investigate the characteristics, attitudes and experiences of the survey participants (1996 policy).
Qualitative Research
Focus of Research • Understand and interpret
Researcher Involvement • High researcher is participant
Research Purpose • In-depth understanding
Sample Design • Nonprobability
• Purposive
Sample Size • Small
Data Analysis • Human analysis
Task 3 – Present findings to the board (group).
1) Qualitative Research Methodologies
The research methodology based on the scientific method of quality, the scientific method of modern science. According to Cooper and Schindler (2014), “researchers have chosen a quality approach based on the project’s goals, its schedule, including the speed of understanding it needs, its budget is being investigated, the type of player needed and the research skills, personality and hobbies” (p. Quality research is under investigation for the purpose of understanding social and human-based issues based on the natural environment. In quality research, there were many concepts of fact that were subject to bias and the researchers were, because of this research, actively involved in the process of research and data analysis, thereby building a sense of complex computations of the reporting process (Gravier, 1994, pp. 1, 2). This type of method is used depending on the type of question or problem that needs to be answered (Imel, Kerka and Wonacott, 2002). Marshall (2006) concludes that quality studies usually rely on four methods of concentration. There are several ways to collect quality data.
Focus groups
Interviews
Observation
Archival material
Focus groups
Focus groups are a common method of collecting quality data. In this way, a group of people are asked about their attitudes and experiences on the subject. Questions are limited to group mergers that participants are free to talk with other members of the group. In general, the focus group is led by an experienced facilitator. The main focus group is interviewing 6 to 10 people in a group discussion of questions and answers. Some of the benefits of the focus group are that it can collect information about a lot of people in a single session, and it can be a focus group or an informal group. The disadvantage is that the focus group can be more responsive and lead to problems with the composition, and the participants are less willing to show personal data in the focus group. Focus group interviews are a research approach that is widely used in social science. “One of the many types of group interviews contradicts individual interviews or didadichni, including a small group of interviews, usually between four and eight people, including focus talk talks and is directed by a training facilitator .From one to two hours, and often involving specific to stimulate discussion (objects, pictures Etc.), the goal is to maintain the interaction between the members of the group on the subject of focus, not to work with the didadichen questions- and interaction between interviews and in tervyuiranite .Focusing groups are useful especially when researchers seek to find different ways people experience social phenomena sharing through Discussion “(Sto and Lunt, 2011).
Structured and informal interviews are two types of interviews. Structured interviews have pre-defined questions. Informal interviews go with this flow of conversations and generate an impromptu question, but the research must be able to avoid conversations to focus on the subject you want. Some of the benefits of structured interviews allow data collection to be monitored efficiently and conveniently in the process of synthesis and analysis. Disadvantages of structural adjustment have been reduced to an unexpected response. Second, the goal of the interview can affect data collection and bias. Informal interviews are an advantage that can hinder geometry from creating data collection. Second, it can generate unexpected information when the interview is not specifically designed against the interviewer. The disadvantages of informal interviews are not comparable and data can not be summarized. Informal interviewing generally takes a long time to be analyzed and analyzed. Finally, informal interviews can put a lot of pressure on the interviewer to ask questions and investigations on the spot. “The interview of this study, one of the most important qualitative methods for collecting the data have been used extensively for Ethnographic Research and field studies. Even when it’s not the first method of data collection in quantitative research methods of interview is often used as a pilot study to collect data Primary sector before the study is done, “Qu and Dumay (2011).
2) Observation
Monitoring is a tracking process to collect data based on the conclusions. For example, a researcher can go to school and watch a teacher or school counselor. Observations concerning observers to note the attitudes and actions of individuals or groups. The benefits of this data are timely recording of information and unusual details can be noted during observation. Disadvantages that may not be able to use all data due to confidentiality. The presence of researchers may influence the behavior of the participants. Researchers may not have the expertise to monitor and observe. Monitoring includes the full scope of activity monitoring activities and behavior and behaviors. The surveys can be classified as follows:
Non-behavioral Observation
• Record analysis
o Analysis of historical or current records and public or private records.
• Physical condition analysis
o Audits of merchandise availability, studies of plant safety compliance, etc
• Physical process analysis
o Time/motion studies, financial flows in a banking system, paper flow in office systems, etc.
Behavioral Observation
• Nonverbal analysis
o Monitoring eye movement in user-interface studies.
• Linguistic analysis
o Study of a sales presentation’s content or the study of what, how, and how much information is conveyed in a training situation.
• Extralinguistic analysis
o Study of the linguistic content of the interaction between supervisors and subordinates.
• Spatial analysis
o Study of how salespeople physically approach customers.
Archival Material
Document Papers is a collection of public documents, such as newspapers, minutes, meetings, official reports, magazines, letters and e-mails for data collection purposes. The benefits give the researcher access to information in the words of the participants by saving the time and cost for the transcript.
Qualitative Method Strengths and Weaknesses
Some disadvantages are that information may be protected and not accessible for public or private access, information that may be difficult to find material may not be complete and invalid files. Research limitations, some limitations to quality, generally small-scale research, need cognition, language, and endurance. It takes a long time, the research can not be summarized, often determined in the tradition presented and difficult to synthesize the study.
Limitations of Qualitative Research
• Strengths
– Participatory
– Rich, detailed data
– Considers users perspectives and the context for their behaviors
• Weaknesses
– Hard work
– Time consuming
– Smaller sample of users
– Not easily verified
– Not easy to group responses and categorized
Quantitative
Research in education is a natural manifestation of the nature and methods used to do this research, it is often seen as a quantitative method, but the quality has become more general in recent years (Smeyers, 2008). The description often uses statistical and digital data. It can also be used in scientific experiments, surveys and structural observations. A quantitative study does not require personal interpretation, so it must be reproduced by anyone. For example, a researcher wants to know what is the best leading chemical fertilizer brand on sunflower. Researchers will start with hypotheses, for example, that brand A is the best. Researchers will test a lot of fertilizers on the sample size of plants, carefully check the atmosphere and measure all plants. If the findings of the researcher are true, other researchers will have the same result as a repeat test. According to Shelley (2006), “a quantitative survey begins with the idea that to measure something, especially in digital form, to better understand it.” The collected data is collectively called “data.” What is measured is variable, which means simply changing something in the value of repeated observations. Individual or student teachers, districts, public or other entities whose data is collected. ” Quantitative study includes numerical data analysis. The quantitative purpose is to investigate the relationship between this variable. Variable is one of the characteristics and is against three independent independent independent dependencies. Independent variables are organized by the researchers. Dependent variables are characteristics influenced by the preparation of independent variables. The external variable is variable, the extremists that the researchers are trying to concentrate and are generally demographic information such as age, gender and ethnicity. Quantitative research refers to objectivity, strict control of the research status and the ability to make common findings.
3)
Volume also aims to hypothesize assumptions, check causes and effects, and make predictions. “A quantitative survey was used to measure and predict, as a result, in the final course of action. Quantitative studies are usually based on the use of rigorous projects and statistical analysis to generate their findings. The five basic concepts that are based on the application of quantitative research, internal and external validation testing hypothesis and the importance of copying and general ability “(Haertel, 2010). The measurement is negative, so be explicit and specific measures.” Ask for social issues or based on tests, in theory, the composition of the variables measured by the number and analyzing procedures Statistics to determine whether the predictions of theoretical summary of this is true (Creswell, 1994). “Quantitative research shows the possibility of replication” (Cohen, Manion & Morrison, 2003). The overall goal of educational research is to explain and predict the attitudes or relationships between education areas (Smith 1983). The quantity is marked by the collection and analysis of systematic data and the input of tools and measurements to choose from. The results can provide a comprehensive and useful answer for any case, institution or individual. Graneheim & Lundman (2003) pointed out that a quantitative method, which is often used in media research, and that quality content is applied to education in education.
Quantitative Research
Focus of Research • Describe
• Explain
• Predict
Researcher Involvement • Limited
• Controlled to prevent bias
Research Purpose • Describe or predict
• Build and test theory
Sample Design • Probability
Sample Size • Large
Data Analysis • Human analysis
Quantitative Research Emphasis
• Emphasis on collecting and analyzing information in the form of numbers;
• Emphasis on collecting scores that measure distinct attributes of individuals and organizations; and
• Emphasis on procedures of comparing groups or relating factors.
According to Bhanot (2009), quantitative approaches to support decision-making. Emphasis is not on their own approach, but the way they can contribute to a better solution than the methodology is to describe the situation where the quantitative methods have been successfully implemented, and then show how managers can use better decision-making approaches. “It shows how quantitative methods help managers in their daily decision-making. In the past, they relied on the feeling of the majority decision. Now, they can use a combination of experience and their quantitative methods to make better decisions. The quality of the decisions that have shown remarkable improvement After using these methods (Bhanot, 2009).
Limitations of Quantitative Research
• Cannot predict who will get disease
• Usually will not tell how to fix a problem
• Can help ranking problems but do not tell which problem to address first
• Insufficient by itself to make a decision
Quantitative Method Strengths and Weaknesses
• Strengths
– Robust
– Objective
– Verifiable
• Weaknesses
– Out of context human behavior, real world settings are not considered
– Any variables left out of data collection are not used in analysis
–
Task 4 – Individual analysis and Assessment
Hypothesis Testing
Hypothesis is a statement or refers to the relationship between the variables between the groups that can be tested. «Quantitative techniques are used for hypothesis testing, the determination of the relationship between variables (or values that can be changed), and measuring the frequency (number) of the notice” (Chan, 2002). As a quantitative method that is used to test the hypothesis. “The test of this hypothesis is the traditional method to assess the statistical significance Of the results of quantitative research. This method allows for a very realistic comparison of the observed findings of the sample detection, if the hypothesis is empty. The hypothesis tests allow researchers to calculate the likelihood that the observed results were caused by accident, “he said (Haertel, 2010). Analysts should check and make a hypothesis and test alternative hypotheses proud. The research generally begins with a common problem. The first hypothesis, a hypothesis proud of this option can help investigators by providing Chu Some kind of comment and review, particularly on this issue. In the definition of Aliaga and Gunderson (2000): A quantitative study “to explain this phenomenon by collecting numerical data, which are analyzed using mathematical methods.”
Hypothesis testing seeks to answer seven questions:
1. What are the null hypothesis and the alternative hypothesis?
2. Which test statistic is appropriate, and what is the probability distribution?
3. What is the required level of significance?
4. What is the decision rule?
5. Based on the sample data, what is the value of the test statistic?
6. Do we reject or fail to reject the null hypothesis?
7. Based on our rejection or inability to reject, what is our investment or economic decision? (Investopedia, 2014)
In today’s companies, companies can use the regression hypothesis to solve a question that needs to be held accountable. According to Duane and Seward (2007), bi-equation regression is a flexible way to analyze the interrelationships between two quantitative variables that can help answer practical questions. The use of a test for the hypothesis of regression bi-equivalence is known in some businesses to investigate policy issues about the company, leading business interactions smoothly and efficiently. However, the case study will use data from the wage and salary data set to create a research question and formulate a hypothesis where it can be tested with linear regression analysis. Using a set of data on wages and salaries, the results of linear regression analysis from the collected data will also be prepared. Next, the next step is to perform and interpret the results of the hypothesis regression test.
Hypothesis Statement
By using the Wages and Wage Earners data set conducting a two-tailed test to determine if age has any association with wages earned. The null hypothesis and the alternative hypothesis for the test are as follows:
H0: β0 = 0 (age is associated with wages earned).
H1: β0 ≠ 0 (ages is not associated with wages earned).
Test for the zero intercept of 100 observations of wages earned and the ages of the wage earners. The research question like to answer is whether or not the age of the wage earner has a positive or negative association with wages being earned. A regression hypothesis test will be performed to determine if the null hypothesis is to be accepted or rejected.
Regression Hypothesis
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.16665
R Square 0.027772
Adjusted R Square 0.017851
Standard Error 16795.15
Observations 100
ANOVA
df SS MS F Significance F
Regression 1 7.9E+08 7.9E+08 2.799417 0.097488
Residual 98 2.76E+10 2.82E+08
Total 99 2.84E+10
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 22047.71 5513.092 3.999155 0.000123 11107.16 32988.26 11107.16 32988.26
Age 224.6421 134.2633 1.673146 0.097488 -41.7991 491.0833 -41.7991 491.0833
The above regression is, X=Wages earned and Y = the ages and n = 100 the observations. The regression fitted equation is, y = 224.64x + 22047.71. The degree of freedom equals 99 – 1 = 98, critical value of t corresponding to 98 degree of freedom at α = 0.05 (two – tailed test) is 1.9842. Since the t-value is 1.6731 and is less than the critical value of 1.9842, the null hypothesis is accepted. The 95% confident that the true population slope lies between -41.7991 and 491.0833. It is verified from the output that F = (t^2) for the slope of (t^2) = 1.6731^2 = 2.799417 ͌ 2.80 = F. Since the p-value for X = Wages are less than 0.05, the variables have a significant influence in the given regression. “Hypothesis testing provides a basis for taking ideas or theories that someone initially develops about the economy or investing or markets, and then deciding whether these ideas are true or false. More precisely, hypothesis testing helps decide whether the tested ideas are probably true or probably false as the conclusions made with the hypothesis-testing process are never made with 100% confidence – which we found in the sampling and estimating process: we have degrees of confidence – e.g. 95% or 99% – but not absolute certainty” (Investopedia, 2014).
t-Test: Paired Two Sample for Means
Wage Age
Mean 30833.46 39.11
Variance 287204106 158.0584848
Observations 100 100
Pearson Correlation 0.1666498
Hypothesized Mean Difference 0
df 99
t Stat 18.1731118
P(T<=t) one-tail 1.3238E-33
t Critical one-tail 1.66039116
P(T<=t) two-tail 2.6476E-33
t Critical two-tail 1.9842169
Data in Graphical Format Figure 1- Scatter plot graph of the regression equation ..
The range of the way is designed to show a link between two variables by graphs on a series of observations on two-dimensional graphic diagrams along the X axis, and the other along the Y axis (Investopedia, 2014). Interpretation The Blue Regression Test Result is used to determine whether the employee’s age is positive or negative based on salary. Although the author has done it, the two-way discussion service is a flexible way to analyze the relationship between the quantitative variables, there are some restrictions for double regression testing. A double regression is only used when calls for a simple pattern. In addition, regimen testing has been used by bivalitniyat, which has few impact predictors, but a logical prediction and a position within itself is very good (Doan and Dad, 2007). In order to determine the regression equation is y = 224.64x + 22047.71 with the level of freedom 98. The results of the bivariate regression test carried out both tests with α in terms of 0.05 = allowed to accept empty hypotheses. This is due to the price t-1.6731, which is less than the key value of 1.9842. Therefore, as a result, it has been found that at a 95% confidence level, the true slope of the population is between -41.7991 and 491.0833.
The hypothesis should be accepted for H0 since t – the confirmation value and the result of the plane F = (T ^ 2) of the slope of (T ^ 2) = 1,673 ^ 2 = 2,799417 2,80 = female is the same as the F value at the output. T-Pricing Tests can be used to answer questions that investigate whether the employee’s age is positive or negative depending on the wage. The answer is found in this issue, the salary age is positive and negative, depending on payroll. Collected and used are used to evaluate the results of this data collection set. Overall, a regression analysis is used to apply various techniques for variable analysis and modeling, especially when it is related to one or more variables or between an independent variable-dependent.
The use of hypothetical tests has helped to reduce the ruptive error of reliance on the quality of the case. Regression hypotheses can be used to make clear what is likely to lead to regression in the data set for wages and salaries. So using the bivariata hypothesis, the hypothesis of regression to determine the answer is that age has a positive relationship with the salary that has occurred. Determine that this independent variable is the wage that is received and the dependent variable is the age of the recipient. Using the methods of independent variables and variables relies on the relationship between these two variables, the reason for choosing a binary regression. The findings suggest that wage hires, data sets and salaries are enough to help us, which are used to reach the final result of this hypothesis. In this case, we accept the hypothesis that wages are positively linked to the age of workers.
Side-by-Side Comparison Chart
Quantitative vs. Qualitative Research
Quantitative Qualitative
Level of occurrence Depth of understanding
Asks “how many” or “how much” Asks “why”
Studies events Studies motivation
Objective Subjective
Discovery and proof Enables discovery
More definitive Exploratory in nature
Describes Interprets
Conclusion
The quantitative method may have additional benefits, even if data is unskilled for scientific experiments that do not require a contribution or case study of personality, personality, behavior, and behavior (Lunenburg & Irby, 2008). There are several standards that can be used to evaluate quality and quantitative research, which is contributing to good writing theory and definite precision and methodology (Pratt, 2008). However, while the purpose of quality research can be agreed, the means of assessing the methodology and the quality are unavailable and is not available with publication constraints. Pratt (2008) argues that quality statements are more enjoyable to regulators by following a quantitative model of quantitative or quantitative content.
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