Premium Essay

Level of Confidence

In:

Submitted By jowshel
Words 997
Pages 4
Elements of poem

SPEAKER is the imaginary voice assumed by the writer of a poem. In many poems the speaker is not identified by name. When reading a poem, remember that the speaker and the poet are not the same person, not more than an actor is the playwright. The speaker within the poem may be a person, an animal, a thing, or an abstraction.
A STANZA is a formal division of lines in a poem, considered as a unit. Often the stanzas in a poem are separated by spaces. Stanzas are sometimes named according to the number of lines found in them.

a. 2 lines ---- couplet

b. 3 lines ---- tercet

c. 4 lines ---- quatrain

d. 5 lines ---- cinquain

e. 6 lines ---- sestet

f. 7 lines ---- heptastich

g. 8 lines ---- octave

Rhythm: This is the music made by the statements of the poem, which includes the syllables in the lines. The best method of understanding this is to read the poem aloud. Listen for the sounds and the music made when we hear the lines spoken aloud. How do the words resonate with each other? How do the words flow when they are linked with one another? Does sound right? Do the words fit with each other? These are the things you consider while studying the rhythm of the poem. METER of a poem is its rhythmical pattern. This pattern is determined by the number and types of stresses, or beats, in each line.
Rhyme: A poem may or may not have a rhyme. When you write poetry that has rhyme, it means that the last words of the lines match with each other in some form. Either the last words of the first and second lines would rhyme with each other or the first and the third, second and the fourth and so on. Rhyme is basically similar sounding words like ‘cat’ and ‘hat’, ‘close’ and ‘shows’, ‘house’ and ‘mouse’ etc. Free verse poetry, though, does not follow this system. Or RHYME is the repetition of sounds at the ends of

Similar Documents

Premium Essay

Makhoya

...according to the six car types. The mpg variables of mpg town and mpg best are also to be grouped according to the six car types. The Analysis Toolpak in Tools within Excel is then to be used to create tables for the price variables showing all descriptive statistics with the mean, median, standard deviation, range, skew measure, standard error, sum, count and coefficient of variation which is to be manually added in one table. There is to be an interpretation at the end of each table which includes concerns about the differences in the mean prices and mean mpg across vehicle types and the possible causes depending on whether it’s a mpg or price table. The distribution of price and mpg shapes across each vehicle type and what it means. Confidence intervals are to be used to talk about prices in the population of cars. Several differences of means tests on both prices and mpg are to be taken where there is no much difference between the means of different car types, in both prices and mpg. To find the likelihood of a cheap car of an efficient car across categories probability is to be used and its pattern is to be tested using chi squared tests. The second aim is to predict the mpg. This is to be done by using correlation to look for linear...

Words: 3076 - Pages: 13

Premium Essay

Mnmproject3

...* Construct a 95% Confidence Interval for the proportion of blue M&Ms’ candies. Solution: The confidence interval is given as p±z1-α2 p1-pn where, p represents the proportion of success=proportion of blue M&Ms’ candies=0.213944 n represents sample size=9194 Z1-α2for 95% confidence level=1.96 Therefore, the required Confidence Interval is given as p±z1-α2 p1-pn =0.213944±1.960.2139441-0.2139449194 =0.213944±0.008383 =(0.205561, 0.222327) * Construct a 95% Confidence Interval for the proportion of orange M&Ms’ candies. Solution: The confidence interval is given as p±z1-α2 p1-pn where, p represents the proportion of success=proportion of orange M&Ms’ candies=0.214596 n represents sample size=9194 Z1-α2for 95% confidence level=1.96 Therefore, the required Confidence Interval is given as p±z1-α2 p1-pn =0.214596±1.960.2145961-0.2145969194 =0.214596±0.008392 =(0.206204, 0.222988) * Construct a 95% Confidence Interval for the proportion of green M&Ms’ candies. Solution: The confidence interval is given as p±z1-α2 p1-pn where, p represents the proportion of success=proportion of green M&Ms’ candies=0.183163 n represents sample size=9194 Z1-α2for 95% confidence level=1.96 Therefore, the required Confidence Interval is given as p±z1-α2 p1-pn =0.183163±1.960.1831631-0.1831639194 =0.183163±0.007907 =(0.175256, 0.821070) ...

Words: 722 - Pages: 3

Free Essay

Business Intelligence

...exercise we will concern ourselves with only seven different classes. Using a minimum support threshold of 30% and a minimum confidence level of 60%, (manually) apply association rule mining to the set of transactions given below to identify all valid rules. Clearly list out all relevant steps and report the support, confidence and lift for each valid rule that you generate. Customer ID 1 2 3 4 5 6 7 8 9 10 Food Yoga, Pilates, Weight Loss, Step Aerobics Zumba, Cardio, Weight Loss, Spinning Yoga, Zumba, Pilates, Step Aerobics Yoga, Pilates, Step Aerobics Zumba, Cardio, Spinning Step Aerobics, Spinning, Weight Loss Zumba, Pilates, Yoga Yoga, Spinning Pilates, Step Aerobics Step Aerobics, Pilates, Spinning Solution 1] Given: A) Minimum Support Threshold = 30% B) Minimum Confidence level = 60% Applying Apriori Algorithm:   Support greater than the user-specified support threshold min_sup (minimum support) , and Confidence greater than the user-specified confidence threshold min_conf (minimum confidence) Formulae to be used: a) Support = No of Transactions containing all items in antecedent and consequent transactions in the database. / No of b) Confidence = No of Transactions containing all items in antecedent and consequent No of transactions containing items in the antecedent. c) Lift = Confidence of the Rule / / Support of the Consequent. 1. One Element sets validity check: Step 1 – First look for most frequent...

Words: 1287 - Pages: 6

Premium Essay

Swag

...Lab 61: Confidence Intervals on Proportions In this lab you're going to use the simulation at http://statweb.calpoly.edu/chance/applets/Reeses/ReesesPieces.html to take virtual samples of Reese's pieces (sorry no real chocolate) Open up the simulator and set π = .3. This is really p, but on my screen it comes out as π, set Sample Size, n = 30 . This means we are setting the proportion of orange Reese's pieces as .3 When you click on "Select Sample" the computer will pull 30 Reese's pieces, and put them in bins as orange, yellow, and dark brown and it will tell you p for orange. What you're going to do is repeatedly sample, using the simulator, and after each sample calculate confidence intervals for confidence levels of 60%, 80% and 99%. You'll (ok, the computer, will do a total of 20 samples). Then we'll see how many confidence intervals at each level contain the actual population proportion. Some formulas and items you will need: CI = p± z*σ, where σ=p(1-p)n Remember that p can be given in the problem or a calculated p. Use the simulator to find p , then calculate the rest to fill in the table. For this lab, σ= .084 If you calculate the # orange, you can use stat-tests-1propZint on your calculator Sample # | p orange | # orange = 30p | 60% Confidence Interval z*=.84 | 80% Confidence Interval z*=1.28 | 99% Confidence Interval z*=2.58 | | | | Min | Max | Min | Max | Min | Max | 1 | | | | | | | | | 2 | | | | | | | ...

Words: 563 - Pages: 3

Premium Essay

Market Risk Mgt Through Var

...VALUE AT RISK VaR is a predictive (ex-ante) tool used to prevent portfolio managers from exceeding risk tolerances that have been developed in the portfolio policies at a certain confidence level under normal market conditions. The usual holding periods are one day or one month. The confidence level is intuitively a reliability measure that expresses the accuracy of the result. The higher the confidence level, the more likely we expect VaR to approach its true value or to be within a pre-specified interval. Analytical VaR is also called Parametric VaR because one of its fundamental assumptions is that the return distribution belongs to a family of parametric distributions such as the normal or the lognormal distributions. Analytical VaR can simply be expressed as: | | where: * VaRα is the estimated VaR at the confidence level 100 × (1 - α)%. * xα is the left-tail α percentile of a normal distribution . xα is described in the expression  where R is the expected return. In order for VaR to be meaningful, we generally choose a confidence level of 95% or 99%. xα is generally negative. * P is the marked-to-market value of the portfolio. Objectives of VaR measurement * It facilitate risk reporting and control decisions. * The simplicity of VAR measurement greatly facilitated dealers’ reporting of risks to senior managers and directors. * VAR also proves useful in dealers’ risk control efforts. * Commercial banks, use VAR measures to quantify...

Words: 1126 - Pages: 5

Premium Essay

Mat 300 M&M Project 3

...Part 3 (21 pts) We will be constructing confidence intervals for the proportion of each color as well as the mean number of candies per bag. You will use the methods of 6.3 for the proportions and 6.1 for the mean. For the Bonus, you will use the sample size formula on page 338. You can use StatCrunch to assist with the calculations. A link for StatCrunch can be found under Tools for Success in Course Home. Here is also a link: http://statcrunch.pearsoncmg.com/statcrunch/larson_les4e/dataset/index.html. You can also find additional help on both confidence intervals and StatCrunch in the Online Math Workshop under Tab: “MAT300 Archived Workshops”. Specifically you will be looking for Confidence Intervals and Using Technology – CI. Submit your answers in Excel, Word or pdf format. Submit your file through the M&M® project link in the weekly course content. If calculating by hand, be sure to keep at least 4-6 decimal places for the sample proportions to eliminate large rounding errors. Answers 3 pts. Construct a 95% Confidence Interval for the proportion of blue M&Ms® candies. 95% Confidence Interval for proportion is given by [pic] where p = x/n = 810/4049 = 0.200049395, [pic]= 1.959963985, n = 4049 Therefore, CI is given by, [pic] = (0.187727588, 0.212371202) Thus with 95% confidence we can claim that the proportion of blue M&Ms® candies is within (18.77%, 21.24%). Details |Confidence Interval Estimate for Proportion ...

Words: 1133 - Pages: 5

Premium Essay

Ois-Quiz Study for Chapter 8 and 9

... |ID#: |Section#: |Serial#: | Show your work in detail and write neatly and eligibly 1. A 95 percent confidence interval estimate will have a margin of error that is approximately + 95 percent of the size of the population mean. Answer: False 2. Increasing the sample size will result in a point estimate that is closer to the true population value. Answer: False 3. In estimating a population proportion, the factors that are needed to determine the required sample size are the confidence level, the margin of error and some idea of what the population proportion is. Answer: True 4. The margin of error is: a. the largest possible sampling error at a specified level of confidence. b. the critical value times the standard error of the sampling distribution. c. Both a and b. d. the difference between the point estimate and the parameter. Answer: C 5. An intern working for a food processing company has submitted a report in which he says that the company should use a sample size of 460 to estimate the mean weight of a packaged product. The report further states that the confidence level would be 95 percent and that he has assumed that the population standard deviation for the product weights is 0.3 pounds. However, he did not state anything about the margin of error that was used. Based on the above information...

Words: 717 - Pages: 3

Free Essay

Consumer Confidece Index

...“A STUDY ON CONSUMER CONFIDENCE INDEX FOR THE RESIDENTS OF CITY LUDHIANA” MAJOR RESEARCH PROJECT Submitted to PUNJAB TECHNICAL UNIVERSITY In partial fulfillment of Requirement for degree of MASTER OF BUSINESS ADMINISTRATION BY SARGAM NAGRATH (University Roll no- 1335890) DEPARTMENT OF MANAGEMENT PUNJAB COLLEGE OF TECHNICAL EDUCATION BADDOWAL, LUDHIANA AFFILIATED TO: Punjab Technical University, Jalandhar 2013-2015 CERTIFICATE This is to certify the thesis/dissertation entitled ‘Consumer Confidence Index For The Residents Of City Ludhiana’ submitted for the degree of M.B.A in the subject of Finance of the Punjab Technical University is a bonafide research work carried out by Sargam Nagrath (MBA HR & Finance), University Roll no( 1335890) and no part of this thesis/dissertation have been submit by any other degree. The assistance and help received during the course of investigation have been fully acknowledged. Major Advisor: Mrs. Pallavi Dawra ...

Words: 14450 - Pages: 58

Premium Essay

Jjklj

...Correlation Correlation is a statistical technique that can show whether and how strongly pairs of variables are related. For example, height and weight are related; taller people tend to be heavier than shorter people. The relationship isn't perfect. People of the same height vary in weight, and you can easily think of two people you know where the shorter one is heavier than the taller one. Nonetheless, the average weight of people 5'5'' is less than the average weight of people 5'6'', and their average weight is less than that of people 5'7'', etc. Correlation can tell you just how much of the variation in peoples' weights is related to their heights. Although this correlation is fairly obvious your data may contain unsuspected correlations. You may also suspect there are correlations, but don't know which are the strongest. An intelligent correlation analysis can lead to a greater understanding of your data. Techniques in Determining Correlation There are several different correlation techniques. The Survey System's optional Statistics Module includes the most common type, called the Pearson or product-moment correlation. The module also includes a variation on this type called partial correlation. The latter is useful when you want to look at the relationship between two variables while removing the effect of one or two other variables. Like all statistical techniques, correlation is only appropriate for certain kinds of data. Correlation works for quantifiable data...

Words: 2286 - Pages: 10

Premium Essay

Statistic

...condominium sales as well as residential land and homes and commercial properties in the Navarre Area. When you stay with Gulf Properties, you are supporting local business and independent property owners that keep our beaches beautiful and our community strong. The confidence interval (also called margin of error) is the plus-or-minus figure usually reported in newspaper or television opinion poll results. For example, if you use a confidence interval of 4 and 47% percent of your sample picks an answer you can be "sure" that if you had asked the question of the entire relevant population between 43% (47-4) and 51% (47+4) would have picked that answer. The confidence level tells you how sure you can be. It is expressed as a percentage and represents how often the true percentage of the population who would pick an answer lies within the confidence interval. The 95% confidence level means you can be 95% certain; the 99% confidence level means you can be 99% certain. Most researchers use the 95% confidence level. When you put the confidence level and the confidence interval together, you can say that you are 95% sure that the true percentage of the population is between 43% and 51%. The wider the confidence interval you are willing to accept, the more certain you can be that the whole population answers would be within that range. For example, if you asked a sample of 1000 people in a city which brand of cola they preferred, and 60% said Brand A, you can be very certain...

Words: 580 - Pages: 3

Premium Essay

Stats Week 5 Quiz

... | the t distribution with n + 1 degrees of freedom | | | the t distribution with n + 2 degrees of freedom | 5 points    QUESTION 2 1. An estimate of a population parameter that provides an interval of values believed to contain the value of the parameter is known as the | | confidence level | | | interval estimate | | | parameter value | | | population estimate | 5 points    QUESTION 3 1. The value added and subtracted from a point estimate in order to develop an interval estimate of the population parameter is known as the | | confidence level | | | margin of error | | | parameter estimate | | | interval estimate | 5 points    QUESTION 4 1. Whenever the population standard deviation is unknown and the population has a normal or near-normal distribution, which distribution is used in developing an interval estimation? | | standard distribution | | | z distribution | | | alpha distribution | | | t distribution | 5 points    QUESTION 5 1. The z value for a 97.8% confidence interval estimation is | | 2.02 | | | 1.96 | | | 2.00 | | | 2.29 | 5 points    QUESTION 6 1. The t value for a 95% confidence interval estimation with 24 degrees of freedom is | | 1.711 | | | 2.064 | | | 2.492 | | | 2.069 | 5 points    QUESTION 7 1. As the sample size increases, the margin of error | | increases | | | decreases | | | stays the same | | | increases or decreases...

Words: 595 - Pages: 3

Premium Essay

Value at Risk

...Undergraduate Research Opportunity Programme in Science Value at Risk Dai Bo Supervisor: Dr. Arie Harel Department of Mathematics National University of Singapore Academic year (2000/2001) I Summary Value at Risk (VaR) is one of the most popular tools used to estimate exposure to market risks, and it measures the worst expected loss at a given confidence level. In this report, we explain the concept of VaR, and then describe in detail some methods of VaR computation. We then discuss some VaR tools that are particularly useful for risk management, including marginal VaR, incremental VaR and component VaR. The next consideration is the effect of time varying risk, which can be estimated by a moving average model or a GARCH process. Finally, we introduce some back testing methods to validate the use of VaR model. All description, definitions, examples, results, proofs, tables, and remarks in this report are taken from the 2nd edition of the book of Philppe Jorion “Value at Risk” (Jorion 2001), unless otherwise indicated. II Table of contents Cover page I Summary II Table of contents III Chapter 1 Motivation and Introduction 1 1.1 Motivation 1 1.2 Introduction 1 1.3 Overview of the report 2 Chapter 2 VaR computation 3 2.1 Definition of VaR 3 2.2 Measuring returns 3 2.3 Computation of VaR 4 2.4 VaR measurement over different parameters 9 2.5 Choice of parameters 10 ...

Words: 3437 - Pages: 14

Premium Essay

Regression

...Construct a Confidence Interval Instructions on the left Instructions on the right pertain to means pertain to proportions 1. POPULATION a. Identify the parameter of interest: π : proportion µ : Mean Numerical (Measurement) Categorical (success-failure) b. Describe the variable in context with the problem: µ = mean of the amount of drying time of a particular paint. π = proportion of people in the community who prefer smoking 2. STATISTICAL METHOD a. Determine the confidence level (1 - α) and the level of significance α . NOTE: If not specified, set the confidence to 0.95 (95%) and the level of significance to 0.05. b. Identify the required formula for the confidence interval: When σ known: ⎛ σ ⎞ x ± ( zcriticalvalue )⎜ ⎟ ⎜ ⎟ ⎝ n ⎠ p ± ( zcriticalvalue ) p (1 − p ) n When σ unknown: ⎛ s ⎞ x ± (tcriticalvalue )⎜ ⎟ ⎜ ⎟ ⎝ n⎠ 3. SAMPLE a. Calculate or identify the descriptive statistics: Descriptive statistics needed: • the sample mean • standard deviation • sample size b. Check the conditions for normality: population is normal OR n ≥ 30 Descriptive statistics needed: • the sample proportion • sample size np ≥ 10 AND n(1 − p ) ≥ 10 www.rit.edu/ASC Page 1 of 2 4. STATISTICAL RESULTS a. Find the required z or t critical value: z critical value: 1. Find α Same as z critical value information on the left. 2 2. Take this value and locate it in the standard normal probability table and identify the z critical value. NOTE: Commonly used z critical value Confidence Level...

Words: 395 - Pages: 2

Premium Essay

Contents of a Business Proposal

...independence between rows and columns. The chi-square test is based on the assumption that you already know 3 numbers: the row proportions, the column proportions and the totalt number of observations. Since the total number of number in your table is 4, and 3 were already known before you started to compute the chi-square statistic, the degrees of freedom is 4-3=1. Now the theory says that you must use the chi-quare table with one degree of freedom. Confidence Level A confidence level refers to the likelihood that the true population parameter lies within the range specified by the confidence interval . The confidence level is usually expressed as a percentage. Thus, a 95% confidence level implies that the probability that the true population parameter lies within the confidence interval is 0.95. Here, the confidence level (95%) implies a probability equal to 0.95 Significance Level A Type I error occurs when the researcher rejects a null hypothesis when it is true. The probability of committing a Type I error is called the significance level, and is often denoted by...

Words: 283 - Pages: 2

Premium Essay

Gulf Real Estate Properties

...includes: 1. Appropriate descriptive statistics to summarize each of the three variables for the forty Gulf View condominiums 2. Appropriate descriptive statistics to summarize each of the three variables for the eighteen No-Gulf View condominiums 3. Comparison of your summary results from #1 & #2. Discuss any specific statistical results that would help a real estate agent understand the condominium market. 4. A 95% confidence interval estimate of the population mean sales price and population mean number of days to sell for Gulf View condominiums. Also, interpret the results. 5. A 95% confidence interval estimate of the population mean sales price and population mean number of days to sell for Gulf View condominiums. Also, interpret the results. Also, consider the following scenario and include your responses in your Report: 6. Assume the branch manager requested estimates of the mean selling price of Gulf View condominiums with a margin of error of $40,000 and the mean selling price of No-Gulf View condominiums with a margin of effort of $15,000. Using 95% confidence, how large should the sample sizes be? GULF VIEW CONDOMINIUMS List Price Sales Price Days to Sell 495000 475000 130 379000 350000 71 529000 519000 85 552500 534500 95 334900 334900 119 550000 505000 92 169900 165000 197 210000 210000 56 975000 945000 73 314000 314000 126 315000 305000 88 885000 800000 282 975000 975000 100 469000 445000 56 329000 305000...

Words: 913 - Pages: 4