These tools are widely used by local economic development (LED) practitioners: General tools to help organise and compare data: Time series analysis Growth indexes Composite indexes Benchmarking GIS mapping PEST / trends analysis Tools to help cities understand the structure of their local economy: Sector share analysis Value-added analysis Economic base analysis Location quotient Specialisation index Shift share analysis Input-output analysis Social accounting matrix Cluster mapping Value chain
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Business (Report) Writing Clear Technical Writing provides a step-by-step process for designing and writing a clear technical document, whether it be an engineering, email or scientific report. You will learn by doing, the only legitimate way to improve writing skills! The training involves writing, revising, and editing exercises; critiquing documents; games; and lecture. You will walk away with confidence in writing and editing skills and a consciousness about international writing. Top
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process of Education. In the present day, each person including the students and the teachers face anxiety, frustration, etc. Due to these factors, the students cannot keep much interest in their study, academic activity & their performance in the entire exam. Consequently, in this way it is very essential for the students to keep their eyes in their study & academic activity. For the outcome of this predicament, ‘YOGA’ is the recent and excellent way. That is 34 International Journal for Research
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Interval | | 2. T – test | to compare the means when the population mean is known but the population variance is unknown.Also when the population standard deviation is unknown but the sample standard deviation can be computed.Source:Basic Statistics Book | OrdinalInterval | | 3. F – test | used when comparing statistical models that have been fitted to a data set, in order to identify the model that best fits the population from which the data were sampled.Source:http://en.wikipedia.org/wiki/F-test
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lurch. Our regression analysis looks at comparing two factors only, an independent variable and dependent variable (Murembya, 2013). Benefits and Intrinsic Job Satisfaction Regression output from Excel SUMMARY OUTPUT Regression Statistics Multiple R 0.018314784 R Square 0.000335431 The portion of the relations explained Adjusted R Square -0.009865228 by the line 0.00033% of relation is Standard Error 1.197079687 Linear. Observations 100
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One of the most basic statistical analysis is descriptive analysis. Descriptive statistics can summarize responses from large numbers of respondents in a few simple statistics. When a sample is obtained, the sample descriptive statistics are used to make inferences about characteristics of the entire population of interests. Descriptive analysis is the transformation of data in a way that describes the basic characteristics such as tendency, distribution, and variables. A examples of this would be
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Hypothesis Testing – Two Sample * H0 : µ1 = µ2 H1 : µ1 ≠ µ2 * Case 1 -- If you know population variances, use this and Normal table * Case 2 -- If you know only sample variances, and samples are large, use this and Normal table * Case 3 -- If you know only sample variances, and samples are small, and unknown population variances can be assumed identical, use this and t-table, with n1 + n2 - 2 df. (sp is called “pooled estimate of σ”) * We use standard error
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M.Marks:60 SECTION A Note: - Attempt any 4 questions. All questions carry equal marks. (4 X 5) The answer should be limited upto 200 words. 1) What is statistics? Explain the nature and limitations of statistics? 2) What is frequency distribution? What are the different types of frequency distribution? 3) What is frequency curve? Explain cumulative frequency curve with example? 4) Suppose mean of a series of 5
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β3. Estimated equation is: Log (wage) = 0.128 + 0.0904educ + 0.041exper – 0.000714exper2 (0.106) (0.0075) (0.0052) (0.000116) n = 526, R2 = 0.30 ii) Yes, the coefficient is significant because t-statistics absolute value 6,16 is greater than t (critical value) at 1 % significance level which is 2,586 in this case. iii) Return to the fifth year of experience: 100 * [0.041-2*(0.000714)*4] = 3,53% Return to the 20th year of experience: 100 *
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LLR 1st Quarter Report Project Name: Address: Project Manager: Area Manager: Staff Team: Volunteers: Contents 1. Introduction 2. Service Activity 3. Referrals 4. Outcomes 5. Engagement 6. Incidents 7. Feedback 8. Staff Development 9. Project Development 10. Conclusion 1. Introduction This report is based on the activities undertaken by ------- for the period
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