Free Essay

Descriptive Stats Analysis

In: Business and Management

Submitted By mkeller26050
Words 1631
Pages 7
Barbara Tucker who oversees Ballard Integrated Managed Services, Inc for the Douglas Medical Center location decided to conduct a survey in regards to the research question asking, why the turnover rate jumped from averaging 55-60% to 64%. A survey was given to each employee of BIMS that support the Douglas Medical Center and of the 5,300 employees only 78 participated in the survey leaving a very low response rate or 17.3%. This immediately tells the observers that the morale of the employees is not very high and one can only hope that the information provided by the 78 employees helps to point to why they are feeling this way. The following information will show how the responses were computed using descriptive statistics in the form of tables, charts, measures of central tendency, and variability.
In regards to the charts created from the responses to the survey, some inferences can be made and some conclusions can be drawn. One such inference could be that since more than half of the employees participating in the survey replied that they do not enjoy working for BIMS, this could also be a realistic ratio for the whole staff as many did not feel that it was important enough to respond to the survey. Another inference could be that the managers and supervisors are not reacting to the scheduling needs of their employees from the beginning of their employment. This could be concluded because 51 of 78 responses were negative in regards to, if the employees felt their request for their desired shift was fulfilled. A staggering revelation from the charts and what may be the most compelling as to why the companies has such a high turnover rate is in reference to the question regarding if the employees feel they are paid fairly for their work. There were 50 responses that were of the two most negative response options in the survey, and not one employee chose the highest option of very positive. From the information provided in the charts an observer can conclude that due to the lack of manger and supervisor support of the needs of the employees, and lack of fair pay, the employees simply do not enjoy working for BIMS and will leave as soon as they get an opportunity to, through new employment.
Measures of Central Tendency
After careful scrutiny, our team has revised our initial assessment of the nature of the BIMS survey data and has come to the conclusion that the survey is, in fact, qualitative in nature. Questions 1-10 are ordinal, because the categories assigned can be ordered or ranked; questions A, C, and D, are demographic in nature, and, thus, nominal, because the categories do not have an intrinsic order (in addition, questions C and D are dichotomous). We have also calculated the measures of central tendency (mean, median, and mode) for the survey data and are able to reach some interesting conclusions. First of all, we stand by our original assessment that the data retrieved BIMS was not enough to reach any definitive conclusions about what the majority population of the BIMS employees feel, but, in the absence of returned surveys, we ‘crunched’ the numbers, so to speak, and came up with the following:
• The value that was most used by respondents was number two, which has been identified as “Somewhat Negative,” with value one, “Very Negative,” second. To give these numbers some sort of contextual reference, more responses were number two, the frequency of which is higher than possible responses four and five, the more positive responses, combined. See histogram A. Histogram A
• We have calculated that the central tendency (mean, median and mode) for each of the ordinal questions (Question 1-10) and see that, again, the tendency is for the numbers to fall under the value of three—which has been identified as “Neither Positive nor Negative.” The best measure of central tendency for ordinal data, the median, show that for Questions 1,3,5,and 7, the median value is three; for Questions 2,and 4, the median is two point five; for Questions 6,8,9, and 10, the median is two. Again, we must note that numbers do not lie; the central tendency is for the respondents to be either neutral or less than positive about their employment at BIMS. Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10
MEAN 2.807692 2.730769 2.807692 2.769231 2.884615 2.064103 2.871795 2.653846 2.217949 2.653846
MEDIAN 3 2.5 3 2.5 3 2 3 2 2 2
MODE 2 2 2 2 2 2 2 2 2 2

In using the Ballard Integrated Managed services inc.,Members of the BIMS were asked to answers each question from 1-10, with rating from very negative to very positive with one be the same as rating of one to five. Colum’s one on the data represents the 78 members and column 2 represent the question 1-10. We also recorded zero when some members did not answers the questions and also recorded 6. The first table is a table of numerical questions in the BIMS data. Team B, focus on three top most important questions such as do you enjoy working for BIMS, if you are paid fairly and do you fear your job.
When asked for Question 1, “How well do you enjoy working for BIMS?” On the negative side 1 employees did not answers, About 15 of the employees rate very negative , About 21% rate negative , 12% rate neutral , which that shows more employees are very unsatisfied about working for BIMS. Only 2 employees rate positive to that question.
When asked for question 6, you are paid fairly for the work you do? , about 3 employees did not answer, 20 employee rate very negative, 30 employee rate negative , 19 employees was neutral about it , 6 employees rate positive and nobody rate positive. Again only 6 employees rate positive and very positive means nobody believe they get paid fairly. It is important to know how satisfied the employees feel about their pay.
When as for question 10, Do you fear that you will lose your job?, 2 did not rate , 17 rate very negative, 22 rate negative, 12 rate neutral, 15 rate positive and 9 Rate very positive. As for that question, not a lot fear for their job.
When ask questions from A, in which division do you work? The answers were between (1) Food, (2) Housekeeping (3) Maintenance, we had to count as code, 1 or 2 or 3. About 32 employees work for Food services, 36 employees work for housekeeping and 9 employees work for Maintenance. For question B, asked how long you have working for BIMS? For example B, there were different complete answers to pick from months and years because it ranges from 1 month to 328 months. For the fourth table C, what is your gender? Was from either female or Male and the table shows there was 27 female and 38 male. The last table which is D, Are you a manager or supervisor, the answers was either yes for manager and no for supervisor. There were a total of 12 managers and 63 supervisors. BIMS EMPLOYEE SURVEY
NA Very Negative Negative Neutral Positive Very positive
(0) (1) (2) (3) (4) (5) (6)
Question 1-10
Q1 1 15 21 12 12 1 1
Q2 2 14 22 13 14 11 1
Q3 1 15 21 15 13 13 0
Q4 3 15 21 12 12 12 2
Q5 1 13 22 14 14 14 0
Q6 3 20 30 19 6 0 0
Q7 0 15 21 15 13 14 0
Q8 4 15 22 12 13 10 1
Q9 0 17 32 24 5 0 0
Q10 2 17 22 12 15 9 1

N0. Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10
0 1 2 1 3 1 3 0 4 0 2
1 15 14 15 15 13 20 15 15 17 17
2 21` 22 21 21 22 30 21 22 32 22
3 12 13 15 12 14 19 15 12 24 12
4 12 14 13 12 14 6 13 13 5 15
5 1 11 13 12 14 0 14 10 0 9
6 1 1 0 2 0 0 0 1 0 1

Answers for A

Division FOOD SERVICES Housekeeping Maintenance 32 36 9

Answers for C Gender Female 1 Male
27 38

Answers for D Job Title Manager / Supervisors = Yes Non- Manager / Supervisors = No
Yes 12
NO 63

If and even there is a huge adequate sample size, there will still need to be more information to arrive at a conclusion. A measure of variability is what is needed. Typically, if you hand out 449 surveys employees you expect to get all 449 surveys back. Will everyone return the surveys back who work in housekeeping, food or maintenance? Male or Female? Understanding how the data is spread will show us how efficient the survey is. If each person in housekeeping returns their survey, then it will be obvious the survey has had a positive outcome, however, when workers contain a broad variability with the percentage of the returns (most likely they will), the image will then become a bit fuzzy. A proper conclusion can only be made if the mean and variability has been calculated. In his case, if the survey returns are large and there is little variability, then we would receive a p-value (probability-value) that is small. According to Merriam-Webster probability-value is the probability of an event or outcome in a statistical experiment (Merriam-Webster, 2014).


Similar Documents

Premium Essay

Real Estate Analysis

...REAL ESTATE DATA Team E QRB 501 May 5, 2011 Larry Oslund REAL ESTATE DATA SET Real estate investment can be risky if the buyers are not aware of the different types of houses structures ranging from commercial, residential, apartment complex, single houses, or duplex. Moreover, the attributes of how many beds/baths, the proximity from the main city and freeways, and the area they located are crucial factors in the buying decision. Based 105 houses being surveyed, we can determine their pricing values according to the given variables: size, distance from the city, bedrooms, township, pool, baths, and garage. Variable Analysis PRICE ROBERT’S please attach what we came up with in class. See Appendix A GARAGE Based on the given data set, we can say that most houses being surveyed have at least one garage. 31% of the houses have no garages and 71% have 1 garage. The maximum of garage a house can have is one and the minimum is none. See Appendix H DISTANCE Distance from the center of the city to each of the 105 houses was measured in miles and had a range from a minimum of six miles to a maximum of 28 miles. The average distance was fifteen miles and the most common distance was sixteen miles from the center of the city and 85% of the 105 houses were within twenty miles of the city center. Although not true for every property, in general, the properties farther away from the city tend to be priced less than the properties......

Words: 873 - Pages: 4

Premium Essay

Nba Statistics

...Table of Contents Introduction……………………………………………………………………………………………………………………2 Descriptive Analysis and Frequency Distribution…………………………………………………………….2 Hypothesis Testing………………………………………………………………………………………………………….7 Hypothesis 1…….……………………………………………………………………..……………………......7 Hypothesis 2……………………………………………………………………………………………………...8 Hypothesis 3……………………………………………………………………………………………………...9 Multiple Regression Analysis…………………………………………………..…………………………………….11 Summary ……….…………………………………………………………………………..………………………………..16 Reference……………………………………………………………….…………………………………………………….19 Appendices……………………………………………………………………….…………………………………………..20 Introduction For my statistical data analysis project, I chose to analyze the National Basketball Association (NBA) 2013 regular season teams. The analysis looks at the total team and reviewed the information such as games played, field goals attempt and percentage, free throw attempts and percentage, blocks and steals. The data was obtained from the NBA website. For the 2013 NBA stats there were 30 teams that played on the average of 82 games. Based on statistical analysis, the most important keys for team success in basketball and their relative weights, in parentheses, are field goal percentage, turnovers, offensive rebounds, free throw attempts and percentage, blocks and steals. Coaches are always looking for a better understanding of what makes up a winning team. This knowledge would help them improve the team statistics in the areas......

Words: 3661 - Pages: 15

Premium Essay

Minitab Tutorial

...STAT582 HW7 Review of Two Statistical Software Packages – Minitab and SPSS Yan Sun As a statistician, have you ever got stuck in front of your computer, trying to figure out the correct syntax of a command to type into the little programming window, and just could not get it right? At that moment, I am sure you would wish there was some magic easy button that you could just click and then things would work the way they should. Well, magic does not happen everyday. However, some better choices can make life easier. Instead of using programmed command lines, some statistical software make their usage much easier by using a menu-driven interface. This kind of software are like well-organized control panels. Each of the things you need to do is controlled by a button somewhere on the panel. Once you get familiar with the layout of the panel, the actual work should be quite an enjoyable process. Several good menu-interface statistical software are available. Among them, Minitab and SPSS are the most widely used ones. This report serves as an introduction to these two software packages. For each of them, the software’s specialties, advantages, and suitability will be discussed. Some important functionalities, their implementations, and programming in the two software will be introduced. This report also includes ‘helpful resources’, which I personally found very helpful in learning and using the two software. 1. Minitab History Minitab......

Words: 3780 - Pages: 16

Premium Essay

Mpact of Workforce Diversity on Organizational Performance in the Education Sector of Karachi Pakistan

...IMPACT OF WORKFORCE DIVERSITY ON ORGANIZATIONAL PERFORMANCE IN THE EDUCATION SECTOR OF KARACHI PAKISTAN 1Hafiza Sumaiyyah Iqbal, 2Faiza Maqbool Shah (Supervisor) Department of Business Administration, Jinnah University for Women (JUW) Karachi Pakistan ABSTRACT Diversity is gradually used and accepted as a significant organizational resource in esteems to whether the objective is to be an employer of choice, to offer outstanding customer service, or to sustain a competitive advantage. It also has verified to have controlled to an opinion of being essential for organizational performance. This ultimate faith forces managers to hold and understand the theory of workplace diversity, its benefits and barriers. The purpose of this research is to discover the impact of diversify workforce towards organizational performance which focus into the education sector. The research also emphases on workforce diversity which contains the gender, ethnic and education background of the employees which is the utmost critical variables amongst all the others. The research was done by distributing 100 questionnaires to the faculty members of 5 different universities of Karachi. The questionnaire outcomes show that there is an impact on performance when diverse workforce is working in the education sector. Key words: Workforce Diversity, Organization, Performance, Gender, Ethnic, Qualification, Karachi,......

Words: 7503 - Pages: 31

Premium Essay

Qa Quiz

...2 Broad Study in Statistics Descriptive (mô tả) : provides simple summaries about the data collected & about the preliminary observations that have beed made. Such summaries maybe either quantitative (numerical measures) or visual (e.g. simple-to-understand graphs) e.g. Present a summary report of this year business result to management Inferential (suy luận) : are systems of procedures that can be used to draw conclusions from datasets arising from systems affected by random variation. The type of inferential statistical procedure used depends upon the type of data collected as well as the distribution of the data. The procedures are usually used to test hypotheses and establish probability. e.g. Estimate the IQ score of Kaplan students by observing a small group of students Population : e.g. A population is a collection of all individuals, objects, or measurement of interest Sample : e.g. A sample is a portion or part of the population of interst MCQ 1. The process of using sample statistics to draw conclusions about true population parameters is called Statistical inference. Keywords: inferential statistics 2. Those methods involving the collection, presentation, and characterization of a set of data in order to properly describe the various features of that set of data are called Descriptive statistics. 3. The collection characteristics of the employees of a particular firm is an example of Descriptive statistics. 4. The estimation of the......

Words: 1655 - Pages: 7

Premium Essay


...Analysis of Newspaper Research Report Sandra Nelson HCS/438 10/24.2011 Dr. Jill Wiseberg Analysis of Newspaper Research Report This paper will give an analysis of statistical study involving the eating disorders of teens. Eating disorders are more widespread in teens than formally thought, and has had a devastating effect on their lives, a study for the Archives of General Psychiatry revealed the widespread disorder and behaviors in 10,123 teenagers between the age of 13and 18. The study disclosed that out of the 10,123, about 0.3% had anorexia, 0.9% developed bulimia, and 1.6% practiced binge eating disorders. Nearly all teen with social impairment have anorexia as an eating disorders and theses impairment affect their social and family relationship (Park, 2011). What statistical procedures are used in the study? The population chosen was teens from 13 to 18 years, the 10,123 were chosen from the National Co-morbidity Survey Replication Adolescent Supplement. This would be a subset of the population, this element was possible chosen based on the particular study, and this is not a representation of the entire population, in this article the researcher used the empirical method for gathering data. The sampling method is difficult to differentiate, is it systematic or convenience sampling? the advantages of systematic is that it can eliminate other source of bias, the disadvantage would be that bias can be introduce where patterns used for samples coincides with......

Words: 773 - Pages: 4

Premium Essay

Math 553

...balance for our suburban customers is more than $4,300. Testing the hypothesis that the mean annual income was less than $50,000 One-Sample Z: Income ($1000) Test of mu = 50 vs < 50 The assumed standard deviation = 14.64 95% Upper Variable N Mean StDev SE Mean Bound Z P Income ($1000) 50 43.74 14.64 2.07 47.15 -3.02 0.001 Test of mu = 50 vs not = 50 The assumed standard deviation = 14.64 Variable N Mean StDev SE Mean 95% CI Z P Income ($1000) 50 43.74 14.64 2.07 (39.68, 47.80) -3.02 0.002 The manager speculated the average income is less than $50,000, according to my stat P value is lower than alpha(.05) this means that the analysis the manager's claim is supported with a 95% confidence. Meaning that the null hypothesis of average is greater or equal to $50,000 is rejected and the alternative hypothesis is supported. The confidence interval at a 95% confidence is between 39.68,47.80. Testing the hypothesis that the true population proportion of customers who live in an urban area exceeds 40% Test and CI for One Proportion Test of p = 0.4 vs p > 0.4 95% Lower Sample X N Sample p Bound Z-Value P-Value 1 21 50 0.420000 0.305190 0.29 0.386 Test and CI for One Proportion The manager speculated the true population of customers who live in an urban area exceeds......

Words: 587 - Pages: 3

Premium Essay

Descriptive & Inferential Statistics

...Descriptive and Inferential Statistics Presentation Tony Roberson, Amani Wilson, Deandra Cobb, and Lysa Satterwhite PSY 315 November 11, 2013 Melinda Waife Descriptive and Inferential Statistics Presentation Click on link below to review Team D’s presentation. Tony’s Presentation Speaker Notes: Introduction: Please review Prezi Source: Flickr User "unity_creative" To understand the simple difference between descriptive and inferential statistics, all you need to remember is that descriptive statistics summarize your current dataset and inferential statistics aim to draw conclusions about an additional population outside of proposed data (eCaro, 2003). Deandra Statistics in Psychology and its function cannot be taken lightly. The importance ofthe development of psychology would not have been realized if statistics did not play such a crucial role. Important components such as inferential statistics and interactions are dynamic in the study of associations, and affiliations that are essential in psychology.Statistic is the exact phenomenon of nature and it helps in providing a better understanding. Statistics helps in the effectiveness and planning of statistical analysis in any field of study. Furthermore, helps in applicable quantitative data and in presenting complex data in a suitable level, diagrammatic and graphic form for a clear comprehension of the data. Amani Wilson Speaker......

Words: 464 - Pages: 2

Premium Essay

Financial Crisis and Its Impact on Stock Market

...A STUDY OF FINANCIAL CRISIS AND ITS IMPACT ON STOCK MARKET A MANAGEMENT RESEARCH PROJECT SUBMITTED TO DHARMSINH DESAI UNIVERSITY FOR THE PARTIAL FULFILLMENT OF FOR THE DEGREE OF MASTER OF BUSINESS ADMINISTRATION (MBA) SUBMITTED BY CHARMI S. SHAH ROLL NO.: 42 UNDER THE GUIDANCE OF Dr. FALGUNI PANDYA ASSISTANT PROFESSOR (FINANCE) CENTRE FOR MANAGEMENT STUDIES DHARMSINH DESAI UNIVERSITY NADIAD 2014 DECLARATION I hereby declare that the project titled “FINANCIAL CRISIS AND ITS IMPACT ON THE STOCK MARKET” is my own work and I have not copied it from somewhere else. The project report is prepared just as a part of partial fulfillment of MBA programme and no other use of this project will be done. MANAGEMENT RESEARCH PROJECT is a part of syllabus in MBA programme of CMS – DDU , Nadiad, Gujarat. Name : Charmi S. Shah Signature : Date : 21st February, 2014 CENTRE FOR MANAGEMENT STUDIES DHARMSINH DESAI UNIVERSITY CERTIFICATE This is to certify that the Management Research Project has been Carried Out under the theme “FINANCIAL CRISIS AND ITS IMPACT ON STOCK MARKET”. This report is the bonafide work of Ms. Charmi Shah Roll Number 1542 of MBA Semester IV during the academic year 2012-14. Faculty Guide: Prof. Falguni Pandya Date: 21/02/2014 Head of Department: Dr. Naresh Patel Date:21/02/2014 Preface Practical knowledge by way of research is a step to bride up the gap between the theoretical studies of finance and its practicality in the world. Hence......

Words: 16467 - Pages: 66

Premium Essay

Inferential Statistics

...Inferential Statistics QNT/561 September 1, 2014 INFERENTIAL STATISTICS SAT scores from 48 students in a low-performing district were analyzed and a descriptive statistical analysis performed. These students were given individualized SAT coaching and their scores after coaching were compared and analyzed against their scores prior to receiving the individualized coaching. Based on the results of that analysis, we now want to determine whether the findings are indicative of the entire population of SAT taking individuals. Hypothesis: Ho=Individualized SAT coaching did not result in an increase in SAT scores. H1=Individualized SAT coaching did result in an increase in SAT scores. Inferential Statistics Distribution: Normal Regression Statistics | Multiple R | 0.985001 | R Square | 0.970227 | Adjusted R Square | 0.96958 | Standard Error | 13.59259 | Observations | 48 | ANOVA | | | | | |   | df | SS | MS | F | Significance F | Regression | 1 | 276957.9 | 276957.9 | 1499.026 | 9.38E-37 | Residual | 46 | 8498.895 | 184.7586 | | | Total | 47 | 285456.8 |   |   |   |   | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | Intercept | -148.751 | 31.54092 | -4.71611 | 2.26E-05 | -212.239 | -85.2619 | -212.239 | -85.2619 | X Variable 1 | 1.133406 | 0.029274 | 38.71726 | 9.38E-37 | 1.074481 | 1.192331 | 1.074481 | 1.192331 | t-Test: Paired Two Sample for Means | | | |   |......

Words: 458 - Pages: 2

Premium Essay

Testing of Phillips Curve in the Us Economy

...unemployment rate and inflation rate can be observed in the long run thus rendering this concept entirely short run in nature? (Phillips, A.W. cited in Ogbokor, 2005).It would be crucial yet interesting to test the validity of traditional long run Phillips curve as it used as a policy guideline and has had many controversies revolving around it for the same. Objective: Phillips Curve in the Long run: Examining the Long run relationship between unemployment rate and inflation rate in United States using univariate analysis (analysis based on descriptive statistics). Methodology: The data used for analysis has 58 observations collected over the period 1952-2008 consisting unemployment rate and inflation rate of US. It has been collected from Bureau of Labour Statistics and We will make use of statistical tools to test the existence of relationship, if any, between the two variables using the t-statistic and descriptive statistics. Analysis: Unemployment rate and Inflation rate of the US Economy over period 1952-2009: Looking at the above graphs, we see that over the years in the long run, unemployment rate and inflation rate have followed the same...

Words: 561 - Pages: 3

Premium Essay

How to Live Longer?

...How to live longer? An analysis of the impact food consumption and healthcare may have on life expectancy. Econ413 SP2011 Introduction Life expectancy is important not only to individuals but also to the nation. To individuals, longer life expectancy gives people more time in their lives to do things they want and gives them opportunity to see their children and grandchildren grow up. To the nation, studying life expectancy helps the government plan for pension benefits and contributions. I want to analyze the impact of food consumption on life expectancy because today people care about eating healthier and America’s eating habit has been criticized for the consumption of too much unhealthy food. In order to measure the country’s eating habits, I used data over the past 40 years that includes annual meat consumption, fish consumption, milk consumption, fruits and vegetable consumption and etc. I will analyze the life expectancy over 1970-2008 and the corresponding food consumptions over that time period. In addition to eating habits, I believe that the nation’s healthcare spending and GDP are important determinants of life expectancy. Excluding them will result in a biased model. Therefore, I also included healthcare and GDP as independent variables in my analysis. Prior Research and Theory In the past few years, life expectancy and its determinants have been widely discussed in economics. In the U.S., life expectancy rapidly increased in the past century and......

Words: 2986 - Pages: 12

Premium Essay


...1. Introduction Poverty, which is measured by the household income lower than poverty line has been identified as the dependent variable in this project. It is important to know which elements are associated with poverty. The purpose of this paper is to evaluate the key determinants of American household poverty in 1980. The four possible determinants will be analyzed in this project, the average numbers of every family (FAMSIZE), URB is the percent of people live in urban, UR is the level of people have no job over 16 years and the median family income in US dollars (INCOME). Descriptive statistics, correlation and regression will be used in this project. 2. Descriptive statistics Variable | Mean | Median | Mode | VAR | STDEV | URB | 58.76034483 | 66.15 | 0 | 1012.828049 | 31.82495953 | FAMSIZE | 3.140172414 | 3.135 | 2.93 | 0.033377163 | 0.182694178 | UR | 9.293103448 | 8.95 | 5.8 | 10.92696915 | 3.30559664 | INCOME | 19240.43103 | 18512 | N/A | 10889936.04 | 329.990309 | POV | 9.120689655 | 9.05 | 8.8 | 6.230792498 | 2.496155544 | 3. Correlation Correlation and regression are techniques for investigating the statistical relationship between two, or more, variables (Barrow, 2013, pp. 238). * Correlation defines the degree to which there is a linear relationship between pairs of variables. Firstly, it is useful to graph the variables to see if anything useful is revealed. In this case, XY graphs are the most suitable and they are shown in......

Words: 1666 - Pages: 7

Premium Essay

Economic Statistics

...Statistics in Economics The Rivalry: Wins per Season Phillies vs. Mets Throughout the years two teams laid the groundwork for what would be considered one of the greatest rivalries of all time. Baseball is America’s pastime and one of my favorite sports. I decided to do an in-depth statistical analysis of both team’s histories regarding wins since 1965. Surprisingly both teams, the Philadelphia Phillies and the New York Mets, have strong numbers but the Phillies came out on top when comparing both data sets. The Phillies have a mean number of wins at 79.72 and the Mets with a mean of 77.28 wins. So, by looking at these data sets from a comparative angle, the Phillies come out on top with an average of about 2-3 wins per season. Taking a look at the medians, you are able to see that Phillies also have a higher mean of 80.5 wins as opposed to the Mets’ 78 wins. By looking at the easy to find statistical values you are able to see which team has been statistically better throughout the past 45 years. After I took a look at the descriptive statistics I ran three different tests: the F-test, the t-test, and the empirical tests to test for each data set’s normality. The first test that I ran in Excel was the F-test, which is a test comparing statistical models to identify the model that best fits the population from which the data was sampled. My results of the F-test came out with a high variance for each team: the Phillies with 133.41 and the Mets with......

Words: 1058 - Pages: 5

Premium Essay


...Student Name: VR Assignment for IBA Business Statistics IBA134 All numerical calculations and graphs/plots should be done using EXCEL. Student Name: Question 1 What type of survey method the researcher could use and why? What sampling method could the researcher use to select his/her sample and why? What are the variables the researcher would consider collecting data for the purpose of the analysis and why? Identify the data types for the variables. a) The survey method recommended would the personal interview. This would be more labour intensive but has a better opportunity to get the desired information. Whereas other methods such as telephone where a lot of people refuse or self-administered questionaries where the response rate is low. b) The researcher could use the “simple random sample” method. This method would be a better approach to selecting members of the population that would fit the survey criteria. c) Although the question sounds simple ie hours to dollars debt there may be other factors such as does TV hours watched influence the debt owed by mortgages etc. or whether food consumables are increased by hours watched. What type of debt? Variables: Hours spent watching TV – Numerical Dollars total in debt – Numerical Mortgage y/n - Nominal Members included in household that watch TV? - Numerical Members in household that incur the debt – Numerical d) The storage of the data could be of concern so the survey would...

Words: 1716 - Pages: 7