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Words 7123

Pages 29

The current state of the world economy is quite uncertain. Economic statistics that governments and other financial institutions use to project the economy imply that the world economy is shrinking. Since 2008, the state of the American economy has not been attractive. For instance, the United States economy has not registered any significant growth for the last three years. The 2011 second quarter results indicated that gross domestic product improved by 1%. At the same time, there was slight increase in business fixed investment sector. This was mainly attributed to good performance in software and equipment. In general, the economy seems to be headed for recovery (United Nations, 2010).

There were increased product and services exports as well as over growth in consumer spending. Overall federal government spending increased. This was as a result of increased government spending in military. The issue of oil and turmoil in oil producing countries especially in North Africa has contributed negatively to the economy. High energy costs mean that most sections of the economy will experience high production costs. Final products will be more costly to the consumer and thus leading to reduced consumer spending. A broader look at the state of the economy reveals that the economy is headed for a recovery. Most core sections of the economy have begun to register growth meaning that soon the economy will bounce back (United Nations, 2010).

Macroeconomic Snapshots and Forecast

Several surveys have been conducted to determine the financial situation of United States. Executives' sanguinity about the budget has continued to propagate over the past months, rendering to the outcomes of a McKinsey Quarterly survey in the area. This was carried out throughout the week that U.S. stock markets hit their topmost point so far in 2009. More businesses are…...

...Justine joy balberanImportance of Statistics in Different Fields Statistics plays a vital role in every fields of human activity. Statistics has important role in determining the existing position of per capita income, unemployment, population growth rate, housing, schooling medical facilities etc…in a country. Now statistics holds a central position in almost every field like Industry, Commerce, Trade, Physics, Chemistry, Economics, Mathematics, Biology, Botany, Psychology, Astronomy etc…, so application of statistics is very wide. Now we discuss some important fields in which statistics is commonly applied. (1) Business: Statistics play an important role in business. A successful businessman must be very quick and accurate in decision making. He knows that what his customers wants, he should therefore, know what to produce and sell and in what quantities. Statistics helps businessman to plan production according to the taste of the costumers, the quality of the products can also be checked more efficiently by using statistical methods. So all the activities of the businessman based on statistical information. He can make correct decision about the location of business, marketing of the products, financial resources etc…(2) In Economics: Statistics play an important role in economics. Economics largely depends upon statistics. National income accounts are multipurpose indicators for the economists and administrators. Statistical methods are used......

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...skalan så att säga trycks ihop. Det farmgår att segmentet består av 32% män och 68% kvinnor. Descriptives | | Statistic | Std. Error | Q25_Kön | Mean | 1,32 | ,035 | | 95% Confidence Interval for Mean | Lower Bound | 1,25 | | | | Upper Bound | 1,39 | | | 5% Trimmed Mean | 1,30 | | | Median | 1,00 | | | Variance | ,219 | | | Std. Deviation | ,468 | | | Minimum | 1 | | | Maximum | 2 | | | Range | 1 | | | Interquartile Range | 1 | | | Skewness | ,777 | ,182 | | Kurtosis | -1,412 | ,362 | * Variansen är ett spridningsmått som baseras på avvikelser från medelvärdet. Notera här att variansen är medelvärdet av avvikelserna i kvadrat. Alla avvikelser upphöjs med två innan medelvärdet för avvikelserna beräknas. Varians beräknat här från ett urval är en skattning av variansen för en population och är därför endast ett estimat av variansen i populationen. i=1NXi-μ2/ N, s2=i=1N(xi-x)2 Varians ,219 * Standardiserad normalfördelad variabel Vi har på sidan om medelfel konstaterat att medelvärdet av manga olika stickprov är normalfördelade. Varje normalfördelad kurva har en mittpunkt (ett medelvärde). Bredden på kurvan kan beskrivas med måttet standardavvikelse. Vid avståndet ± 1 SD från medelvärdet övergår kurvan från konvex till konkav böjning. μ=i=1NXi /N, x=inxi / n Mean Statistic 1.32 Std. Error ,035 | * Den kumulativa täthetsfunktionen F(x0) är arean under täthetsfunktionen f(x) från det......

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...Date File 1 Chapter One 1) Determine whether the evaluated group is a population or a sample a) Based on a randomly selected group of 500 patients with high cholesterol, it was found that 67% have heart disease. Is this a population or a sample; explain your answer. b) An investigation of 150 randomly selected local restaurants concluded that 42% of local restaurants have serious health code violations. Is this a population or a sample; explain your answer. 2) Determine whether the given value is a statistic or a parameter. c) A researcher determines that 42.7% of all downtown office buildings have ventilation problems. Is this a statistic or a parameter; explain your answer. d) After taking the first exam, 15 of the students dropped the class. Is this a statistic or a parameter; explain your answer. 3) Identify the type of sampling used. e) A tax auditor selects every 1000th income tax return that is received. What type of sample is this and why? f) The name of each contestant is written on a separate card, and the cards are placed in a bag with three names being picked from the bag. What type of sample is this and why? 4) Is the study experimental or observation and why? g) A political pollster reports that his candidate has a 10% lead in the polls with 10% undecided. 5) Select the study that is most appropriate and EXPLAIN WHY it is most appropriate for the study. h) Is the aspirin......

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...Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. STATISTICS FOR BUSINESS AND ECONOMICS 6e ESSENTIALS OF Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. STATISTICS FOR BUSINESS AND ECONOMICS 6e David R. Anderson University of Cincinnati ESSENTIALS OF Dennis J. Sweeney University of Cincinnati Thomas A. Williams Rochester Institute of Technology Copyright 2010 Cengage Learning. All Rights Reserved.......

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...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......

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...Statistical Project Assignment | Statistics for Business & Economics | | DATASET 1: SIMPLE REGRESSION ANALYSIS Variable Definition Xi = Weight of car (pounds) Yi = Price of car ($) 1. (a) Regression Model using X to predict Y Weight and Price of Car Sales | | | | | | | | | | | | | Regression Statistics | | | | | | Multiple R | 0.212585295 | | | | | | R Square | 0.045192508 | | | | | | Adjusted R Square | 0.038951936 | | | | | | Standard Error | 7883.368653 | | | | | | Observations | 155 | | | | | | | | | | | | | ANOVA | | | | | | | | df | SS | MS | F | Significance F | | Regression | 1 | 450055137.6 | 450055137.6 | 7.241725381 | 0.007915154 | | Residual | 153 | 9508567701 | 62147501.31 | | | | Total | 154 | 9958622839 | | | | | | | | | | | | | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Intercept | 9854.041192 | 2894.819474 | 3.404026151 | 0.000847889 | 4135.063875 | 15573.01851 | Weight | 2.843766419 | 1.056751555 | 2.691045407 | 0.007915154 | 0.756058281 | 4.931474557 | Table 1 – Simple Linear Regression Model (Y and X) Simple linear regression equation Ŷi=b0+b1Xi From Table 1, we can see that b0 = 9854.0412 and b1 = 2.8438 Ŷi=9854.0412+2.8438Xi Figure 1 – Scatter Plot – Weight of Car vs Price of Car (b) Interpret the slope b1 measures the estimated change in the average value of Y as a result of...

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...integrates applied business research and descriptive statistics. Students will learn to apply business research and descriptive statistics in making better business decisions. Other topics include examination of the role of statistics in research, statistical terminology, the appropriate use of statistical techniques, and interpretation of statistical findings in business and research. Policies Faculty and students will be held responsible for understanding and adhering to all policies contained within the following two documents: • University policies: You must be logged into the student website to view this document. • Instructor policies: This document is posted in the Course Materials forum. University policies are subject to change. Be sure to read the policies at the beginning of each class. Policies may be slightly different depending on the modality in which you attend class. If you have recently changed modalities, read the policies governing your current class modality. Course Materials Lind, D. A., Marchal, W. G., & Wathen, S. A. (2011). Basic statistics for business and economics (7th ed.). New York, NY: McGraw-Hill/Irwin. McClave, J. T., Benson, P. G., & Sincich, T. (2011). Statistics for business and economics (11th ed.). Boston, MA: Pearson-Prentice Hall. All electronic materials are available on the student website. |Week One: Understanding the Meaning of Statistics ......

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...9971 .9979 .9985 .9989 .07 .5279 .5675 .6064 .6443 .6808 .7157 .7486 .7794 .8078 .8340 .8577 .8790 .8980 .9147 .9292 .9418 .9525 .9616 .9693 .9756 .9808 .9850 .9884 .9911 .9932 .9949 .9962 .9972 .9979 .9985 .9989 .08 .5319 .5714 .6103 .6480 .6844 .7190 .7517 .7823 .8106 .8365 .8599 .8810 .8997 .9162 .9306 .9429 .9535 .9625 .9699 .9761 .9812 .9854 .9887 .9913 .9934 .9951 .9963 .9973 .9980 .9986 .9990 .09 .5359 .5753 .6141 .6517 .6879 .7224 .7549 .7852 .8133 .8389 .8621 .8830 .9015 .9177 .9319 .9441 .9545 .9633 .9706 .9767 .9817 .9857 .9890 .9916 .9936 .9952 .9964 .9974 .9981 .9986 .9990 STATISTICS FOR BUSINESS AND ECONOMICS 11e This page intentionally left blank STATISTICS FOR BUSINESS AND ECONOMICS 11e David R. Anderson University of Cincinnati Dennis J. Sweeney University of Cincinnati Thomas A. Williams Rochester Institute of Technology Statistics for Business and Economics, Eleventh Edition David R. Anderson, Dennis J. Sweeney, Thomas A. Williams VP/Editorial Director: Jack W. Calhoun Publisher: Joe Sabatino Senior Acquisitions Editor: Charles McCormick, Jr. Developmental Editor: Maggie Kubale Editorial Assistant: Nora Heink Marketing Communications Manager: Libby Shipp Content Project Manager: Jacquelyn K Featherly Media Editor: Chris Valentine Manufacturing Coordinator: Miranda Kipper Production House/Compositor: MPS Limited, A Macmillan Company Senior Art Director: Stacy Jenkins Shirley Internal Designer: Michael Stratton/cmiller design Cover Designer:......

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...Date File 1 Chapter One 1) Determine whether the evaluated group is a population or a sample. a) Based on a randomly selected group of 500 patients with high cholesterol, it was found that 67% have heart disease. Is this a population or a sample; explain your answer. ANSWER b) An investigation of 150 randomly selected local restaurants concluded that 42% of local restaurants have serious health code violations. Is this a population or a sample; explain your answer. 2) Determine whether the given value is a statistic or a parameter. a) A researcher determines that 42.7% of all downtown office buildings have ventilation problems. Is this a statistic or a parameter; explain your answer. b) After taking the first exam, 15 of the students dropped the class. Is this a statistic or a parameter; explain your answer. 3) Identify the type of sampling used. a) A tax auditor selects every 1000th income tax return that is received. What type of sample is this and why? b) The name of each contestant is written on a separate card, and the cards are placed in a bag with three names being picked from the bag. What type of sample is this and why? 4) Is the study experimental or observation and why? a) A political pollster reports that his candidate has a 10% lead in the polls with 10% undecided. 5) Select the study that is most appropriate and EXPLAIN WHY it is most appropriate for the study. ...

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...possibilities, it is statistics that is relied upon to find solutions to the problems and help determine what possibilities are truly feasible. Statistics may be best defined as the means by which data is gathered, analyzed, and interpreted to better understand a problem or situation. There are two types of data that can be analyzed in statistics. These are quantitative and qualitative data. Quantitative data deals with actual numbers and percentages, things that can be measured. Qualitative data deals with things which cannot be measured, but only perceived, such as color, texture, or odor. For example, one may say that a painting’s dimensions are 15” by 20”. This is quantitative data. One may then say that the painting’s primary color used is yellow. This is qualitative data. Quantitative data deals with quantity, where qualitative data deals with quality. There are four levels of measuring data in statistics. These levels are, in ascending order of specificity: nominal, ordinal, interval, and ratio. Nominal levels of measurement deal with names and categories. Ordinal levels deal with ordering the data, but no distinguishing observations can be made. On the interval level, data can be ordered in a way that does make sense and make a difference in perception. At the ratio level, meaningful ratios can be made to represent the data at hand. For example, distance works on a ratio level. In business, statistics plays a vital role in the decision making process. Statistics......

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...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......

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...Economics 30330: Statistics for Economics Problem Set 8 - Suggested Solutions University of Notre Dame Instructor: Julio Gar´ ın Spring 2012 Hypothesis Testing (80 Points) 1. Consider the following hypothesis test: H0 : µ ≥ 20 HA : µ < 20 A sample of 40 provided a sample mean of 19.4. The population standard deviation is 2. (a) Create a 95% conﬁdence interval for the mean. We know σ, therefore we should use the z − table. This is a one-tailed (lower tail) test, so the 95% conﬁdence interval will be given then by σ x − z.05 √ , ∞ ¯ n 2 19.4 − 1.65 √ , ∞ 40 The 95% conﬁdence interval is µ ∈ [18.878, ∞). (b) What is the p-value? The p-value is the area in the lower tail. First, we calculate the z-value: z= 19.4 − 20 √ = −1.9 2/ 40 Using the normal table with z = -1.9, p-value =.0287. (c) At α = 0.01, what is your conclusion? p-value > .01, so we fail reject H0 at the 99% level. (d) What is the rejection rule using the critical value? What is your conclusion? c Reject H0 at the 99% level if z ≤ zα =-2.33. In this example, -1.9 > -2.33, so we fail to reject H0 at the 99% level. 2. Consider the following hypothesis test: H0 : µ = 15 HA : µ = 15 A sample of 50 provided a sample mean of 14.5. The population standard deviation is 3. 1 (a) Create a 95% conﬁdence interval for the mean. We know σ, therefore we should use the z − table. This is a two-tailed test, so the 95% conﬁdence interval will be given then by σ σ x − z.025 √ , x +...

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...Introductory STATISTICS 9TH EDITION This page intentionally left blank Introductory STATISTICS 9TH EDITION Neil A. Weiss, Ph.D. School of Mathematical and Statistical Sciences Arizona State University Biographies by Carol A. Weiss Addison-Wesley Boston Columbus Indianapolis New York San Francisco Upper Saddle River Amsterdam Cape Town Dubai London Madrid Milan Munich Paris Montreal Toronto Delhi Mexico City Sao Paulo Sydney Hong Kong Seoul Singapore Taipei Tokyo On the cover: Hummingbirds are known for their speed, agility, and beauty. They range in size from the smallest birds on earth to several quite large species—in length from 2 to 8.5 inches and in weight from 0.06 to 0.7 ounce. Hummingbirds ﬂap their wings from 12 to 90 times per second (depending on the species) and are the only birds able to ﬂy backwards. Normal ﬂight speed for hummingbirds is 25 to 30 mph, but they can dive at speeds of around 60 mph. Cover photograph: Hummingbird, Editor in Chief: Deirdre Lynch Acquisitions Editor: Marianne Stepanian Senior Content Editor: Joanne Dill Associate Content Editors: Leah Goldberg, Dana Jones Bettez Senior Managing Editor: Karen Wernholm Associate Managing Editor: Tamela Ambush Senior Production Project Manager: Sheila Spinney Senior Designer: Barbara T. Atkinson Digital Assets Manager: Marianne Groth Senior Media Producer: Christine Stavrou Software Development: Edward Chappell, Marty Wright C iDesign/Shutterstock Marketing Manager: Alex Gay Marketing......

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...CORAL DIVERS RESORT Introduction Coral Divers Resort had a comfortable niche in the scuba diving industry, one that had been enhanced by its owner, Jonathan Greywell's promotional strategy. According to the case study,” over the years, Greywell had established a solid reputation for the Coral Divers Resort as a safe and knowledgeable scuba diving resort. It offered not only a diverse selection of diving activities, but a beachfront location. As a small well-regarded all-around dive resort in the Bahamas, many divers had come to prefer his resort to other, crowded tourists resorts in the Caribbean. "Greywell found this niche by creating short weekend and midweek diving ventures, a service that intrigued the public. Coral Divers Resort has targeted both the aficionado diver, and the tyro, both of which want maximum diving pleasure for minimum expense. The main issue in this case is what Greywell should do to enhance business, which has become increasingly flat. This paper shall consider some of the strategic options open to him, after first performing this abbreviated S.W.O.T. analysis. A classic method of performing competitive analyses of any new, emerging or maturing products the use of a SWOT analysis that stands for Strengths, Weaknesses, Opportunities, and Threats. This analysis of Coral Divers Club will use this method. STRENGTHS * The industry sector (sports diving) is strong and getting stronger.* Greywell has developed a good name and reputation in the industry.*......

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...Descriptive and Inferential Statistics ________________________________________ Statistics can be broken into two basic types. The first is known as descriptive statistics. This is a set of methods to describe data that we have collected. Ex. Of 350 randomly selected people in the town of Luserna, Italy, 280 people had the last name Nicolussi. An example of descriptive statistics is the following statement : "80% of these people have the last name Nicolussi." Ex. On the last 3 Sundays, Henry D. Carsalesman sold 2, 1, and 0 new cars respectively. An example of descriptive statistics is the following statement : "Henry averaged 1 new car sold for the last 3 Sundays." These are both descriptive statements because they can actually be verified from the information provided. The second type of statistics in inferential statistics. This is a set of methods used to make a generalization, estimate, prediction or decision. Ex. Of 350 randomly selected people in the town of Luserna, Italy, 280 people had the last name Nicolussi. An example of inferential statistics is the following statement : "80% of all people living in Italy have the last name Nicolussi." We have no information about all people living in Italy, just about the 350 living in Luserna. We have taken that information and generalized it to talk about all people living in Italy. The easiest way to tell that this statement is not descriptive is by trying to verify it based upon the information provided. Ex....

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