A Hypothesis Is a Claim

, The average diameter of a manufactured bolt is not equal to 30mm ( H1: ? ? 30 ) Challenges the status quo Alternative never contains the â€Å"=†sign May or may not be proven Is generally the hypothesis that the researcher is trying to prove Is the opposite of the null hypothesis e. g. , The average diameter of a manufactured bolt is not equal to 30mm ( H1: ? ? 30 ) Challenges the status quo Alternative never contains the â€Å"=†sign May or may not be proven Is generally the hypothesis that the researcher is trying to prove Is the opposite of the null hypothesis e. g. , The average diameter of a manufactured bolt is not equal to 30mm ( H1: ? ? 30 ) Challenges the status quo Alternative never contains the â€Å"=†sign May or may not be proven Is generally the hypothesis that the researcher is trying to prove If the sample mean is close to the stated population mean, the null hypothesis is not rejected. If the sample mean is far from the stated population mean, the null hypothesis is rejected. How far is â€Å"far enough† to reject H0? The critical value of a test statistic creates a â€Å"line in the sand† for decision making — it answers the question of how far is far enough. Type I Error Reject a true null hypothesis Considered a serious type of error The probability of a Type I Error is ? Called level of significance of the test Set by researcher in advance Type II Error Failure to reject a false null hypothesis The probability of a Type II Error is ? Type I and Type II errors cannot happen at the same time A Type I error can only occur if H0 is true A Type II error can only occur if H0 is false Critical Value Approach to Testing For a two-tail test for the mean, ? known: Determine the critical Z values for a specified level of significance ? from a table or computer Decision Rule: If the test statistic falls in the rejection region, reject H0 ; otherwise do not reject H0 State the null hypothesis, H0 and the alternative hypothesis, H1 Determine the appropriate test statistic and sampling distribution Determine the critical values that divide the rejection and nonrejection regions Collect data and compute the value of the test statistic Make the statistical decision and state the managerial conclusion. If the test statistic falls into the nonrejection region, do not reject the null hypothesis H0. If the test statistic falls into the rejection region, reject the null hypothesis. Express the managerial conclusion in the context of the problem p-Value Approach to Testing -value: Probability of obtaining a test statistic equal to or more extreme than the observed sample value given H0 is true The p-value is also called the observed level of significance H0 can be rejected if the p-value is less than ? Hypothesis Testing: ? Unknown If the population standard deviation is unknown, you instead use the sample standard deviation S. Because of this change, you use the t distribution instead of the Z distribution to test the null hypothesis about the mean. When using the t distribution you must assume the population you are sampling from follows a normal distribution. All other steps, concepts, and conclusions are the same. One-Tail Tests In many cases, the alternative hypothesis focuses on a particular direction H0: ? ? 3 H1: ? 3 This is a lower-tail test since the alternative hypothesis is focused on the lower tail below the mean of 3 H0: ? ? 3 H1: ? 3 This is an upper-tail test since the alternative hypothesis is focused on the upper tail above the mean of 3 Proportions Sample proportion in the category of interest is denoted by p When both X and n – X are at least 5, p can be approximated by a normal distribution with mean and standard deviation Potential Pitfalls and Ethical Considerations Use randomly collected data to reduce selection biases Do not use human subjects without informed consent Choose the level of significance, ? , and the type of test (one-tail or two-tail) before data collection Do not employ â€Å"data snooping† to choose between one-tail and two-tail test, or to determine the level of significance Do not practice â€Å"data cleansing† to hide observations that do not support a stated hypothesis Report all pertinent findings including both statistical significance and practical importance A Hypothesis Is a Claim , The average diameter of a manufactured bolt is not equal to 30mm ( H1: ? ? 30 ) Challenges the status quo Alternative never contains the â€Å"=†sign May or may not be proven Is generally the hypothesis that the researcher is trying to prove Is the opposite of the null hypothesis e. g. , The average diameter of a manufactured bolt is not equal to 30mm ( H1: ? ? 30 ) Challenges the status quo Alternative never contains the â€Å"=†sign May or may not be proven Is generally the hypothesis that the researcher is trying to prove Is the opposite of the null hypothesis e. g. , The average diameter of a manufactured bolt is not equal to 30mm ( H1: ? ? 30 ) Challenges the status quo Alternative never contains the â€Å"=†sign May or may not be proven Is generally the hypothesis that the researcher is trying to prove If the sample mean is close to the stated population mean, the null hypothesis is not rejected. If the sample mean is far from the stated population mean, the null hypothesis is rejected. How far is â€Å"far enough† to reject H0? The critical value of a test statistic creates a â€Å"line in the sand† for decision making — it answers the question of how far is far enough. Type I Error Reject a true null hypothesis Considered a serious type of error The probability of a Type I Error is ? Called level of significance of the test Set by researcher in advance Type II Error Failure to reject a false null hypothesis The probability of a Type II Error is ? Type I and Type II errors cannot happen at the same time A Type I error can only occur if H0 is true A Type II error can only occur if H0 is false Critical Value Approach to Testing For a two-tail test for the mean, ? known: Determine the critical Z values for a specified level of significance ? from a table or computer Decision Rule: If the test statistic falls in the rejection region, reject H0 ; otherwise do not reject H0 State the null hypothesis, H0 and the alternative hypothesis, H1 Determine the appropriate test statistic and sampling distribution Determine the critical values that divide the rejection and nonrejection regions Collect data and compute the value of the test statistic Make the statistical decision and state the managerial conclusion. If the test statistic falls into the nonrejection region, do not reject the null hypothesis H0. If the test statistic falls into the rejection region, reject the null hypothesis. Express the managerial conclusion in the context of the problem p-Value Approach to Testing -value: Probability of obtaining a test statistic equal to or more extreme than the observed sample value given H0 is true The p-value is also called the observed level of significance H0 can be rejected if the p-value is less than ? Hypothesis Testing: ? Unknown If the population standard deviation is unknown, you instead use the sample standard deviation S. Because of this change, you use the t distribution instead of the Z distribution to test the null hypothesis about the mean. When using the t distribution you must assume the population you are sampling from follows a normal distribution. All other steps, concepts, and conclusions are the same. One-Tail Tests In many cases, the alternative hypothesis focuses on a particular direction H0: ? ? 3 H1: ? 3 This is a lower-tail test since the alternative hypothesis is focused on the lower tail below the mean of 3 H0: ? ? 3 H1: ? 3 This is an upper-tail test since the alternative hypothesis is focused on the upper tail above the mean of 3 Proportions Sample proportion in the category of interest is denoted by p When both X and n – X are at least 5, p can be approximated by a normal distribution with mean and standard deviation Potential Pitfalls and Ethical Considerations Use randomly collected data to reduce selection biases Do not use human subjects without informed consent Choose the level of significance, ? , and the type of test (one-tail or two-tail) before data collection Do not employ â€Å"data snooping† to choose between one-tail and two-tail test, or to determine the level of significance Do not practice â€Å"data cleansing† to hide observations that do not support a stated hypothesis Report all pertinent findings including both statistical significance and practical importance

Vulnerabilities in Microsoft Windows Server, IAAS Essay

Vulnerabilities in Microsoft Windows Server, IAAS - Essay Example Cloud computing can be stated as a model for facilitating on-demand, convenient and ubiquitous access to shared pool of computing and configurable resources. This resource sharing platform helps in achieving economies of scale and coherence. The concept of cloud computing is based on a broader aspect of shared services and converged infrastructure. Cloud resources are also dynamically reallocated along with being accessed by multiple users. The entire approach of cloud computing has shifted focus towards OPEX model from basic infrastructure of CAPEX model. This study would reflect upon one of the cloud computing services, known as IAAS. Infrastructure as a service or IAAS is a basic cloud service platform. This mainly refers to online services which abstract user from data partitioning. There are some additional resources offered by IAAS clouds such as raw block storage, firewalls, disk-image library, load balancers, virtual local area networks, software bundles and object storage. W indows Server is a known technology or application based on the concept of IAAS. It is a brand name given to bundle of server operating systems, which are launched by Microsoft. The first server edition was named as Windows NT 3.1; however, there have been advancements in developing Windows Server. This study shall analyse key vulnerabilities witnessed by Windows Server and mitigation strategies implemented over the years. There are some general approaches too that can safeguard the system from external threats.

American Industrial Revolution Pittsburgh, Pennsylvania Essay

American Industrial Revolution Pittsburgh, Pennsylvania - Essay Example These factors all allowed Pittsburgh to become the major American city contributing to the Industrial Revolution, and Pittsburgh's connections with the rest of the United States helped to spawn the Industrial Revolution in other parts of the country. In order to understand why Pittsburgh was such a key player in America's Industrial Revolution, one must trace the city's boom back to the start of the Industrial Revolution within the city's own boundaries. The start of the Industrial Revolution in Pittsburgh can be traced all the way back to the start of the nineteenth century. The low cost of coke, and iron, alongside the large amount of coal found near Pittsburgh contributed to the development of the iron industry within the city, and later, within America (Bernal, 1970, p. 83). Most of the iron production during this time period used charcoal as a source of fuel. However, the discovery of the abundance of minerals around Pittsburgh introduced a new and better way to produce iron. This occurred mainly because coal can create a higher temperature, and is thus more effective for burning in comparison to charcoal. Furthermore, the coal found outside of Pittsburgh was excellent in quality, and was vary abundant (Derry and Williams, 1993, p. 94). For example, coal seams were discovered to be at least four to ten feet in thickness outside the city, and when compared to London, Pittsburgh's coal turned out to be of better quality, more abundant, and most importantly, more profitable. The early production of iron nails, balls, and different farm tools began to occur, and eventually these products were widely available to the public. In 1812, Pittsburgh developed the first iron rolling mill, using the development of the steam engine. This first mill spawned many other mills using steam engine power, and the city grew as a result (Hannegan, 2000, p. 23). By 1815, Pittsburgh could be called the biggest city in the east. This advancement in iron technology in the city opened the door to allowing Pittsburgh to become a major city within the Industrial Revolution. Obviously having better quality coal than London, which was at the heart of the Western Industrial Revolution, is an early indicator of how important Pittsbur gh was becoming to the rest of the United States. The coal developments in Pittsburgh inspired the rest of the United States to revise its approach to goal development. After the development of the iron mills came the development of glass factories, pottery mills, breweries, grist mills, nail mills, steam engine factories, cotton factors, and printing offices. The glass factories were yet another important development to the Industrial Revolution and the rest of the United States. Not surprsingly, plate glass saw very limited residential use in the 1800's. In Boston some of the wealthiest people had begun to use polished plate glass instead of sheet glass in their front windows before 1850. In 1897 the Marsh Plate Glass Company developed a continuous lehr (oven) for annealing plate glass, reducing the carefully controlled cooling time from three days to three hours. Oldhousejournal online