Resource Web Search

Resource Web Search

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Using your favorite search engine, locate online resources that best explain to you particular topics found within your assigned chapter readings for this week. You will need to identify a topic within the chapter you read this week and locate a web resource that best explains the topic to you. For each resource please include the chapter the selected website corresponds to, a functional link to the website, and your rationale for selecting the website.

Chapter 1, “Statistics: The Art and Science of Learning from Data”

These slides have been augmented by your instructor to include tips, hints, include tips, hints, shortcuts, and shortcuts, and instructions on using technology to solve problems in the problems in the homework assignments and on assignments and on exams.exams.
Copyright © 2017, 20013, and 2009, Pearson Education, Inc. 1-3Using Data to Answer Statistical QuestionsSection 1.1
1-4Copyright © 2017, 20013, and 2009, Pearson Education, Inc.The information we gather with experiments and surveys is collectively called data. Example: Experiment on low carbohydrate dietData could be measurements on subjects before and after the experiment.Example: Survey on the effectiveness of a TV adData could be a percentage of people who went to Starbucks since the ad aired.Data and Examples of Collecting Data
1-5Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Statistics is the art and science of: Designing studies Analyzing the data produced by these studies Translating data into knowledge and understanding of the world around us define Statistics
1-6Copyright © 2017, 20013, and 2009, Pearson Education, Inc.The three main components of statistics for answering a statistical question:Design: Planning how to obtain dataDescription: Summarizing the data obtainedInference: Making decisions and predictions Reasons for Using Statistical Methods
1-7Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Design questions:How to conduct the experimentHow to select people for the survey to ensure trustworthy resultsExamples:Planning the methods for data collection to study the effects of Vitamin CFor a marketing study, how do you select people for your survey so you’ll get data that provide accurate predictions about future sales?Design
1-8Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Description:Summarize the raw data and present it in a useful format (e.g., average, charts, or graphs).Examples:It is more informative to use a few numbers or a graph to summarize the data, such as an average amount of TV watchedA graph displaying how a number of hours of TV watched per day relates to the number of hours per week exercising.Description
Inference: Make decisions or predictions based on the data.Examples:Has there been global warming over the past decade?Is having the death penalty as a possible punishment associated with a reduction in violent crime?Does student performance in school depend on the amount of money spent per student, the size of the classes, or the teachers’ salaries?Inference
1-10Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Probability: A framework for quantifying how likely various possible outcomes are.Example: If Brown were actually going to lose the election (that is if he were supported by less than half of all voters), what’s the chance that an exit poll of 3889 voters would show support by 53.1% of the voters?Probability
Copyright © 2017, 20013, and 2009, Pearson Education, Inc. 1-11Section 1.2Sample Versus Population
1-12Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Subjects The entities that we measure in a studySubjects could be individuals, schools, countries, days, etc.We Observe Samples but are Interested in Populations
1-13Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Population: The total set of subjects in which we are interested sample: Subset of the population for whom we have data population and SamplePopulationSample
1-14Copyright © 2017, 20013, and 2009, Pearson Education, Inc.The purpose was to predict the outcome of the 2010 gubernatorial election in California.An exit poll sampled 3889 of the 9.5 million people who voted. Define the sample and the population for this exit poll.The population was the 9.5 million people who voted in the election.The sample was the 3889 voters who were interviewed in the exit poll.Example: An Exit Poll

The purpose was to predict the outcome of the 2010 gubernatorial election in California.An exit poll sampled 3889 of the 9.5 million people who voted. Define the sample and the population for this exit poll.The population was the 9.5 million people who voted in the election.The sample was the 3889 voters who were interviewed in the exit poll.Example: An Exit Poll
1-15Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Descriptive Statistics refers to methods for summarizing the collected data. Summaries consist of graphs and numbers such as averages and percentages.Inferential statistics refers to methods of making decisions or predictions about a population based on data obtained from a sample of that population.Descriptive Statistics and Inferential Statistics
1-16Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Descriptive Statistics ExampleFigure 1.1 Educational Attainment, Based on a Sample of 78,000 Households in the 2013 Current Population Survey.
1-17Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Suppose we’d like to know what people think about controls over the sales of handguns. We can study results from a recent poll of 834 Florida residents.In that poll, 54.0% of the sampled subjects said they favored controls over the sales of handguns.We are 95% confident that the percentage of all adult Floridians favoring control over sales of handguns falls between 50.6% and 57.4%.Inferential Statistics Example
1-18Copyright © 2017, 20013, and 2009, Pearson Education, Inc.A parameter is a numerical summary of the population. Example: Percentage of the population of all Florida residents favoring handgun control.A statistic is a numerical summary of a sample taken from the population.Example: 54.0% of the sampled subjects said they favored controls over the sales of handguns.Sample Statistics and Population ParametersTip: Both parameters and population begin with p.Both statistics and samples begin with s.
1-19Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Random sampling allows us to make powerful inferences about populations.Randomness is also crucial to performing experiments well.Randomness and Variability
1-20Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Measurements may vary from person to person, and just as people vary, so do samples vary. Measurements may vary from sample to sample.Predictions will, therefore, be more accurate for larger samples. Differences between measurements in a larger sample tend to cancel each other out, reducing the overall amount of variation.Randomness and Variability
1-21Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Estimation from Surveys with Random SamplingData from sample surveys is frequently used to estimate population percentages.Example: A Gallup poll recently reported that 30% of Americans worried that they might not be able to pay health insurance costs during the next 12 months.
1-22Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Estimation from Surveys with Random SamplingMargin of error is a measure of the expected variability from one random sample to the next random sample.Example: A margin of error of plus or minus 3 percentage points means it is very likely that the population percentage is no more than 3% lower or 3% higher than the reported sample percentage.
When the difference between the results for two treatments is so large that it would be rare to see such a difference by ordinary random variation, we say that the results are statistically significant. Testing and Statistical Significance
Copyright © 2017, 20013, and 2009, Pearson Education, Inc. 1-24Section 1.3Using Calculators and Computers
1-25Copyright © 2017, 20013, and 2009, Pearson Education, Inc. Using (and Misusing) Statistics Software and CalculatorsMINITAB, JMP, StatCrunch, SPSS, and R are popular statistical software packages on college campuses. The TI-83 +, TI-84, TI-89, and TI-Inspire family calculators, which have similar output, are useful as portable tools for generating simple statistics and graphs. Using Technology The problem is that a computer will perform the statistical analysis you request whether or not its use is valid for the given situation. You, not technology, must select valid analyses. Using Calculators and Computers
1-26Copyright © 2017, 20013, and 2009, Pearson Education, Inc. Data filesLarge sets of data are typically organized in a spreadsheet format known as a data file.Each row contains measurements for a particular subject.Each column contains measurements for a particular characteristic. DatabasesAn existing archive collection of data filesNot all databases give reliable information. Before you give credence to such data, verify that the data are from a trustworthy source. Using Calculators and Computers
1-27Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Your access to the online course materials includes several web apps, organized by chapter.To access these web apps, click Tools for Success and then, under Media, click WebApps.These web apps are useful for performing activities that illustrate the ideas of statistics.You can use web apps instead of StatCrunch or the TI-84 calculator to find solutions to homework and exam problems.When applicable, you can load data from an example given in the PowerPoint lecture. You can also load your own data.The web apps allow you to simulate what would happen in a real-life situation through repeated sampling (without having to collect any data at all)Using Web Apps
1-28Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Example: Calculating an Intervalcontinued
1-29Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Example (continued)continued
1-30Copyright © 2017, 20013, and 2009, Pearson Education, Inc.Example (continued)

Resource Web Search

Sample Solution

 

What was the European Sovereign Debt Crisis? So as to have the option to completely investigate the reasons for European Sovereign Debt Crisis its essential to comprehend what the Crisis is. The beginning of the European sovereign obligation emergency started in Greece where a higher hazard premium was alloted to the Eurozone area. By late 2009 the PIIGS nations (Greece, Spain, Ireland, Portugal and Cyprus) has conceded that their obligation was at a level where they couldn’t reimburse or renegotiate their obligation. In 2010 the International Monetary Fund and pioneers of the Eurozone consented to give a €750 billion salvage bundle to spare these nations from insolvency, the sum was likewise later reexamined to €1 trillion. Driving from this intra-eurozone capital streams at that point fell pointedly, coming about because of a solid fixing of money related conditions because of the emergency. During this emergency a significant number of these nations had their sovereign obligation brought down to garbage status by worldwide credit offices, which further intensified the circumstance. Greece’s degree of obligation being at right around multiple times the level which is ordered by the EU. With obligation levels expected to be topped at 60% Greece’s level was at 113%. Greece and the other PIIGS’s nations obligation were at a level where they required help from an outsider, for example, the (ECB) European Central Bank. In a report it was built up that the towards the finish of 2009 after a Greek difference in government coming about with new government giving a bogus spending deficiency. Which was against EU strategy set in the Maastricht settlement. Toward the start of 2010 Greece has plans to bring down its spending’s deficiency to 3% anyway later in the year Greece let the EU realize that their obligation was at such a level, that they may default. This was a consequence of reckless monetary strategies, and different components. Source: Macrobond, IMF The EU acknowledged to give a crisis bailout bundle as an end-result of Greece actualizing severity measures to manage its degree of obligation which was so crazy. The EU settled on the choice to remain behind its part and help Greece with a bailout bundle, as not rescuing would have gen Resource Web Search uine expenses to the EU all in all. The subsequent somberness estimates expected Greece to cut consumption diminishing the expenses of government community workers. Additionally managing an enormous issue in Greece which is tax avoidance. Coming about because of this a free expense authority was started to help diminish tax avoidance. “In May 2010 a €110 billion gave by euro region Member States and the International Monetary Fund (IMF).” (Powerpoint) These measures additionally expected Greece to auction a huge extent of its state-claimed helps, which was planned to decrease the intensity of associations and gatherings. One of the primary purposes behind Greece’s end was that the regulatory productivity inside Greece was incredibly low. Greece is viewed as a “poor understudy” in the euro zone economy, having a moderately feeble monetary base with a large portion of the populace having low expectations for everyday comforts. Joined with a the very dependence on the travel industry and assembling which was incredibly affected by the Great downturn, Greece’s economy was not fit as a fiddle going into the emergency. For the second PIIG’S nation Ireland. Irelands economy in 2007 had gotten profoundly subject to development and lodging which they utilized as the essential wellspring of monetary development. This was supported by the outside acquiring of Irish Banks as overall loaning rates at the time where generally low. Anyway late 2007 the Irish property bubble began to blast which lead to a decrease in property costs crosswise over Ireland, and lead to a stagnation in property improvement the nation over. This at that point had a move through impact causing huge misfortunes in property advancement and a nation wide breakdown in development action. This causes enormous stain on the nations Irish financial framework, and a gigantic draw again from household property speculator. These banks were regarded too huge to come up short, anyway in 2008 the first of the enormous banks petitioned for section 11 liquidation security. This prompted an arrangement which the Irish government set up to ensure the remainder of the staying national banks. Giving continued liquidity with the goal that more liquidations wouldn’t happen. Matters keeps on compounding and in 2010 the Irish government mentioned help from the EU to abstain from defaulting on its obligation. Spain was a comparative case to Ireland, with a substantial dependence in the property and development indust Resource Web Search ry. The property business expanded exponentially to the point where property turned into the residents favored goal for investment funds. With the Spanish government weighted tax breaks for property which further expanded its venture prevalence. Property estimations kept on expanding, with individuals anticipated that qualities should keep on ascending, without backing off. Essentially, on account of Ireland. One of the key advantages for Spain joining the European Union, was the decrease of loan costs. This significantly expanded to accessibility and access to low financing cost credit. Which prompted a huge scale diverting of capital into the land part. Driving from this the development division turned into an enormous piece of the nations GDP. With it representing 13.3% of the nation’s absolute work. This blast didn’t last anyway prodding from the US monetary emergency, in 2008 the property bubble started to blast. Initially, sparing banks started to fall inside the nation, when markets started to crash. Chapter 11 and awful obligations began to winding out on control. Speculator certainty started to therapist, and government bailouts kept an enormous extent of banks from chapter 11. With the Spanish economy starting to give indications of disappointment, and Bankia which was the fourth biggest bank in Spain falling flat for liquidation. With a large number of the nation’s financial specialists just getting away liquidation through renegotiating there advances ordinarily. From this the pace of economy in Spain start to stagnate in 2008 and began to contract in 2009 and 2010. Once more, to a great extent because of the stockpile of liquidity evaporating globally. Which lead to a breakdown in the Property and development division. This thus at that point lead to wide scale joblessness and putting strain on the nations social security framework. This made the nations obligations get to a level wherein they were fleeing. Which at that point thus required the Spanish government requesting that the EU offer help as the nation’s obligations where at a level where the Spain could make its advantage reimbursements on its open obligation. So also, to other PIIG’S nations the main up to the European sovereign obligation emergency, Italy was at that point generously intensely obligated. To a level where the measure of government obligation surpassed the nations GDP. Which was additionally well over the 60% degree of obligation commanded by the Maastricht settlement. The administration esteemed that this was not an issue for the nation. As the administration had the option to constantly ready to renegotiate this obligation, up until 2010. With the disappointment of the US advertises, this systemically affected the Italian budgetary foundations. This caused a wide scale absence of liquidity, beginning with banks declining to take an interest in between bank loaning because of the absence of money related sufficiency. Prompting a more noteworthy constriction of liquidity. This brought about a droop in the economy’s development because of a bringing down in open utilization and speculation. Fares in the  Resource Web Search nation at that point started to decay with areas, for example, transport and assembling falling by as much as 35%. Italy’s pace of development during the emergency. Year GDP pace of development 2000 5.00% 2001 3.60% 2002 2.70% 2003 3.10% 2004 3.30% 2005 3.60% 2006 4.00% 2007 3.60% 2008 0.90% 2009 – 3.70% 2010 – 0.10% 2011 0.70% Source: Eurostat After a difference in government, Mario Monti Italy’s new executive actualized severe gravity measures. This included decreasing government organization use, raising the retirement age and lessening the degree of tax avoidance. This demonstrated compelling and in view of these measures the financial framework inside Italy just required a little bailout bundle contrasted with other EU nations. During a pressure test led by the ECB in 2011 it indicated that “… the Italian financial framework appears to have low introduction to government obligation; it holds under 10% of household open obligation – against over 40% on account of Spanish banks – just as low presentation to remote sovereign hazard, which speaks to just 23% of the all out government obligation Italian banks hold” (Bolton P, Jeanne O (2011)) The primary driver for Italy being affected by the European sovereign obligation emergency was there overwhelming dependence on open obligation. This turned into a huge issue for the nation in when the monetary atmosphere for the European area started to intensify in 2009. For the remainder of the PIIGS nations Portugal’s hardship began appearing in 2008 when the development of the nation’s economy eased back to a point where it indicated no development. Proceeding to fall in 2009 to a point where it contracted by 3%. Durin Resource Web Search g this time the Portuguese government battled to manage a quickly developing spending shortage, ascending from 2.6% to just shy of 10% in 2009. Looking further into this one of the enormous elements that principle Portugal powerless during the financial downturn was that the nations business has a solid spotlight on creating low worth products, for example, apparel. Indeed, even before the monetary emergency this industry was battling to manage developing challenge from nations, for example, the Philippines and China. Generation proficiency didn’t develop inside the area and the business was quickly losing its upper hand. In the interim the business division was acquiring intensely, which was quickly expanded the nations level of obligation. The Portuguese government kept on spending intensely depend the financial downturn, especially in foundation. At the point when the other southern European nations started to see the impacts of the sovereign obligation emergency global financial specialists>

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