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...approximately equal to the variance of the population divided by each sample's size. This statistical theory is very useful when examining returns for a given stock or index because it simplifies many analysis procedures. An appropriate sample size depends on the data available, but generally speaking, having a sample size of at least 50 observations is sufficient. Due to the relative ease of generating financial data, it is often easy to produce much larger sample sizes. • Null Hypothesis: States the assumption (numerical) to be tested, for Example: The average number of TV sets in U.S. Homes is at least three (H0: μ ≥ 3). 1. Is always about a population parameter, not about a sample statistic. ✓ H0: μ ≥ 3 X H0: [pic] ≥ 3 Always begins with the assumption that the null hypothesis is true, similar to the notion of innocent until proven guilty. Refers to the status quo. Always contains “=”, “≤” or “≥” sign. May or may not be rejected. 1. • The Alternate Hypothesis : Is the opposite of the null hypothesis e.g.: The average number of TV sets in U.S. homes is less than 3 ( HA: μ< 3 ) Challenges the status quo...

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...the following variables (all measured in billions USD) and estimate the corresponding model (Model 1):(Use α=0.05 for references) Yt: Defense budget outlay for year t X2t: GNP for year t X3t: US military sales in year t X4t: Aerospace industry sales in year t D1t: Dummy variable presenting the military conflict involving more than 100,000 troops; D1t=1 if more than 100,000 troops are involved and equal to 0 if fewer than 100,000 troops are involved. |Dependent Variable: Y Sample: 1962 1981 | |Method: Least Squares Included observations: 20 | |Variable |Coefficient |Std. Error |t-Statistic |Prob. | |C |21.40251 |1.496947 |14.29744 |0.0000 | |D1 |-48.21987 |6.871544 |-7.017328 |0.0000 | |X2 |0.013879 |0.003207 |4.328062 |0.0008 | |X3 |0.073146 |0.203805 |0.358902 |0.7254 | |X4 |1.389753 |0.130197 |10.67423 |0.0000 | |X4*D1 |1.540792 |0.325005 |4.740818 |0.0004 | |X2*D1 |0.022406 |0.005781 |3.876038 ......

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... Cases Used All non-missing data are used. Syntax DESCRIPTIVES VARIABLES=Income /STATISTICS=MEAN STDDEV VARIANCE RANGE MIN MAX SKEWNESS. Resources Processor Time 00:00:00.00 Elapsed Time 00:00:00.02 [DataSet0] Descriptive Statistics N Range Minimum Maximum Mean Std. Deviation Statistic Statistic Statistic Statistic Statistic Statistic Three-Year-Average Median Income(2008-2010) 51 $29,453 $36,850 $66,303 $50,734.18 $7,555.310 Valid N (listwise) 51 Descriptive Statistics Variance Skewness Statistic Statistic Std. Error Three-Year-Average Median Income(2008-2010) 57082705.308 .389 .333 Valid N (listwise) EXAMINE VARIABLES=Income /PLOT BOXPLOT STEMLEAF /COMPARE GROUPS /PERCENTILES(5,10,25,50,75,90,95) HAVERAGE /STATISTICS DESCRIPTIVES EXTREME /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Explore Notes Output Created 05-SEP-2012 16:32:55 Comments Input Active Dataset DataSet0 Filter Weight Split File N of Rows in Working Data File 51 Missing Value Handling Definition of Missing User-defined missing values for dependent variables are treated as missing. Cases Used Statistics are based on cases with no missing values for any dependent variable or factor used. Syntax EXAMINE VARIABLES=Income /PLOT BOXPLOT STEMLEAF /COMPARE GROUPS /PERCENTILES(5,10,25,50,75,90,95) HAVERAGE /STATISTICS DESCRIPTIVES EXTREME /CINTERVAL 95 /MISSING LISTWISE ......

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...Unit 1 - Fundamentals of Statistics ReneeCarina Benavente American InterContinental University BUSN311-12005B-11 Abstract In many organizations surveys are done to determine the job satisfaction of their employees. Job satisfaction is important for theses organizations large or small because it makes the aspects of the job easy for employees. Analyzing the data within these surveys is to find the overall job satisfaction using qualitative and quantitative variables. Introduction A word wide study of job satisfaction has been assembled by a large organization called American Intellectual Union (AIU). I have been chosen to be a part of this massive global undertaking. I will be analyzing the data from this study and results survey using AIU’s data set. Chosen Variables In examining the data set and results of AIU’s employees I chose to analyze the positions of the employees as my qualitative variables and the intrinsic job satisfaction as my quantitative variables. I chose to analyze these two specific variables because as an hourly or salary paid employee their internal job satisfaction is very important to know. It is best to understand the job satisfaction of employee position within the organization to better the work environment. Qualitative and Quantitative Variables Using qualitative and quantitative variables you have to know and understand the difference between the two variable or the results would not add up. Quantitative data is data......

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...Exercise: 11 1. What demographic variables were measured at least at the interval level of measurements? Number of hours working per week and Length of labor 2. What statistics were used to describe the length of labor in this study? Were these appropriate? Descriptive Yes, Frequency (30) and mean (14.63) are used to describe the data. 3. What other statistic could have been used to describe the length of labor? Provide a rationale for your answer. Length of labor was described for both the experimental and control groups using means (14.63) and standard deviations (7.78). The exact length of labor was obtained, providing ratio level data that are descriptively analyzed with means and standard deviations. 4. Were the distributions of scores similar for the experimental and control groups for the length of labor? Provide a rationale for your answer. No, the distributions of scores were not similar for the two groups. Experimental group has slightly higher dispersion (n=30 and SD= 7.78) than control group (N=33 and SD=7.2). Standard deviation decreases with larger sample sizes. 5. Were the experimental and control groups similar in their type of feeding? Provide a rationale for your answer. Yes. Bottle-feeding was the mode for the experimental (53.1%) and the control (50%) groups since it was the most frequent type of feeding used by both groups 6. What was the marital status mode for the subjects in the experimental and control groups? Provide both the......

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...Statistical Information Paper I will describe the use of statistic at Veterans hospital in Loma Linda that has 142 Hospital beds and 108 beds of Community Living Center. Employs 2,436 staff. The VA hospital Provided 546,017 outpatients visits in 2008.In 2010 Outpatients visits 584,028 it is increase 38011 or increase 1.07%. Statistics is data use to compare and analysis. Hospital statistics Includes current and historical data on utilization revenue, expenses, person and mush morel Will describe numerical data, numerical count, statically analysis, and four levels of Measurement. Numerical data. Bennett, Briggs, and Troika (2009). Numerical Numerical data is identified, measured, and numerical scale. Numerical data can be Displayed using charts, tables, and graphs. Example I work at medical floor is a busy floor. The Physician is always order many test for the new admit patient. Such as Order the patient, take X-Ray, EKG, CAT scan, GI lab so on. For example, if the patients come back for GI lab.Nurse has To take vital sign every 15 minutes times four, every 30 minutes times two, and one-hour time One. This Vital sign was taken to compare how the vital sign are difference between them. If the vital Sign Drop too low or too high that will nurse alert nurse to check the patient and report to the Physician right away. This entire vital sign nurse has to record in the computer that will show in Line graph. The line graph is easy to...

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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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...Name Instructor’s name Course Date Statistics 1a. P (red ∩ rugged) = P(red)*P(rugged) = 40/200*85/200 = 17/200 b. P (standard) = 46/200 P (not standard) = 1- 46/200= 77/100 P (not standard) = P (DELUXE U RUGGED) = 69/200+85/200 = 77/100 2. P (A) =0.3 P(S) = 0.39 P (M) = 0.63 P (A∩S∩M) = 0.3*0.39*0.63 = 0.07371 ASSUMPTION The events are all independent of each other. 3. P(X=7) 1-(1/8)*(7/8)7= 0.95 b. P(X>7) 1- (1/8)*(7/8)7+ (1/8)2*(7/8)6 = 0.944 5 a Z = x-µ/σ Where the absolute value of z represents the distance between the raw score and the population means in units of standard deviation. b. 42-37/2 = 2.5 p(z>2.5) = 0.9938 a baking of 42 minutes is 2.5 times a standard deviation 0.9938 the mean baking time of 37for a lemon drizzle cake made using this recipe. 6. a. σm = σ/√N = 3.5/√48 = 0.5052 b. µ = 0.5052*48 = 24.2496kg 7. a. scientific hypothesis bH0: maximum weight that can be suspended using each adhesive is different H1: maximum weight that can be suspended using each adhesive is not different c. S.E= √ (σ21/n1 +σ22/n2) = √16.62/38+19.22/46 = 3.907 d. z= statistic – hypothesized mean/estimated standard error but hypothesized mean =0 63.8 – 76.4-0/3.907 = -3.23 P(z>-3.23) = 0.9994 e. assuming we fail to reject the null hypothesis we conclude that maximum weight that can be suspended using each adhesive is different 8. | Regularly watch...

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...The study will require that you examine data, analyze the results, and share the results with groups of other researchers. Job satisfaction is important to companies large and small, and understanding it provides managers with insights into human behavior that can be used to strengthen the company's bottom line. The data set for the study is a sample of a survey conducted on the population of the American Intellectual Union (AIU). It is available via the following link: Excel 2007 DataSet with DataSet Key which contains the following nine sections of data that will be used throughout our course: Gender Age Department Position Tenure Overall Job Satisfaction Intrinsic Job Satisfaction—Satisfaction with the actual performance of the job Extrinsic Job Satisfaction—external to the job, for example, office location, your work colleagues, your own office (cubicle/hard walled office, etc), Benefits—Health insurance, pension plan, vacation, sick days, etc. In the first assignment you are to complete the following: You will need to examine two of the nine sections of data: one section of qualitative data (choose either Gender or Position) one section of quantitative data (choose either Intrinsic or Extrinsic) Each section should include all data points listed in the column for the variable. The requirements include: Identify the data you selected. Explain why the data was selected. Explain what was learned by examining these sets of data.......

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...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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...Statistics Keegan Rodgers QNT/275 1/10/15 Kim Gravelle Statistics There are many types of statistics. At its core though, statistics is; according to the American Statistical Association; “Statistics is the science of learning from data, and of measuring, controlling, and communicating uncertainty; and it thereby provides the navigation essential for controlling the course of scientific and societal advances (Davidian, M. and Louis, T. A., 10.1126/science.1218685).” Business Decisions and Statistics Using statistics for business decision-making is not new. In fact, it’s centuries old. Any time a farmer kept a record of what crops sold at a given price that he then used to adjust his planting the next year, used statistics for a business decision. Today one need only search the database available on the USDA website to access statistics from over 70 years ago. (USDA, 2015) No one can see the future or what it holds. That being said, statistics; if used correctly and with good valid data, it can help eliminate as many guesses as possible to guide the future of a given business. Let’s say, for example, you are a business owner making and selling a widget. The goal is to sell as many widgets as possible at a price that covers the cost of materials, labor and overhead that are needed to make the widgets. Statistics will ensure that you have enough information to make decisions that will have a positive......

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...To investigate if the mean JSL differs between the branches of the company. The data set used for the analysis: Variable | How the variable is measured | Branch | Branches of the company:1= TESS-Nizhnevartovsk, TESS-Kogalym2= TESS Head Office, TESS-Surgut3=TESS-Tyumen, TESS-Khanty-Mansiysk | Number | Number of the respondent | Work_Exp | Work Experience in JSC “TESS”:1= 2 year or less 2= more than 2 years | JSL | Job Satisfaction Level:Ratings from 1 to 5 where 1= very unsatisfied, 5= very satisfied and 0= no answer/blank | 1.2. Revised Data. Test for Normal Distribution To proceed with the analysis it is necessary to determine if the data are distributed normally. The Histogram below as well as the Descriptive Statistics (Appendix 1, Table 1b) show that the data distribution is leptokurtic (kurtosis is 2,021) and negatively skewed (skewness -,240). We can determine several outliers (Appendix 1, Table 1c, Table 1d) with extreme ratios. In cases #46 and #178 JSL is more than the highest option provided in the questionnaire. That could be a mistake in data entering or the respondent wanted to emphasise his/her satisfaction level. These cases were delisted. Cases with “0” responses are to...

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...Graded 1. What demographic variables were measured at least at the interval level of measurement? 2. What statistics were used to describe the length of labor in this study? Were these appropriate? 3. What other statistic could have been used to describe the length of labor? Provide a rationale for your answer. 4. Were the distributions of scores similar for the experimental and control groups for the length of labor? Provide a rationale for your answer. 5. Were the experimental and control groups similar in their type of feeding? Provide a rationale for your answer. 6. What was the marital status mode for the subjects in the experimental and control groups? Provide both the frequency and percentage for the marital status mode for both groups. 7. Could a median be determined for the education data? If so, what would the median be for education for the experimental and the control groups? Provide a rationale for your answer. 8. Can the findings from this study be generalized to Black women? Provide a rationale for your answer. 9. If there were 32 subjects in the experimental group and 36 subjects in the control group, why is the income data only reported for 30 subjects in the experimental group and 34 subjects in the control group? 10. Was the sample for this study adequately described? Provide a rationale for your answer. (Grove 79) Grove, Susan K. Statistics for Health Care Research: A Practical Workbook. W.B. Saunders Company, 022007. VitalBook file. The......

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...Question catalogue: Statistics Self-Study Module Master's programme Media and Communication Science If you are master student of the master programme “Media and Communication Science” and have to fulfill the additional requirement: Self-Study Module Statistics, you have to answer these list of 42 questions. Please answer the following questions concerning statistical methods in social science briefly. Helpful information concerning the questions can be found in the Reader: “Statistics”. Enjoy yourself while answering the questions. Chapter 1 1. A client rates her satisfaction with her vocational counselor on a 4-point scale from 1 = not at all satisfied to 4 = very satisfied. What is the (a) variable, (b) possible values, and (c) score? 2. Give the level of measurement for each of the following variables: (a) ethnic group to which a person belongs, (b) number of times an animal makes a wrong turn in a maze, and (c) position one finishes in a race. 3. Fifty students were asked how many hours they had studied this weekend. Here are their answers: 11, 2, 0, 13, 5, 7, 1, 8, 12, 11, 7, 8, 9, 10, 7, 4, 6, 10, 4, 7, 8, 6, 7, 10, 7, 3, 11, 18, 2, 9, 7, 3, 8, 7, 3, 13, 9, 8, 7, 7, 10, 4, 15, 3, 5, 6, 9, 7, 10, 6 Make (a) a frequency table and (b) a frequency polygon. (c) Make a grouped frequency table using intervals of 0-5, 6-10, 11-15, 16-20. Based on the grouped frequency table, (d) make a histogram and (e) describe the general shape of the distribution. 4. Below are the number......

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...Christian Worldview/Statistics Integration Paper Kevin Lee BUS-352 November 14, 2014 Statistics helps decision makers by transforming collected information into numbers. It allows decision makers to understand the risks associated with decisions that has or been made. Statistic collects, summarizes, presents, and analyzes data. Then it uses its data to help reach conclusions. It is crucial for statisticians to collect data carefully and fairly for importance of finding great value. To have a correct statistic data, it is necessary to have high-top work ethics. Statisticians must take a full responsibility of fairly collecting a data with interest of collecting a valuable data to make the best decisions. Statisticians should not favor any particular data. Statistics must apply Christian worldview principles of trust and honesty. It is an important standard to have for collecting statistic data. The numbers in collected data must be truthful. Utilitarianism ethical theory is most applicable for me. It’s about sacrificing few to save many. The Trolley Problem could be a supportive theory for the utilitarianism. The problem tells about a speeding train with full of passengers sees that there are few workers standing in on the rail road up ahead. To save those few, should the train hit the hard break which will kill all the passengers; or should they run over the few to save many in the train? Utilitarianism theory would support an idea of sacrificing those few to save......

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