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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 of minutes it took each of a group of 10-year-olds to do a series of abstract puzzles: 24, 83, 36, 22, 81, 39, 60, 62, 38, 66, 38, 36, 45, 20, 20, 67, 41, 87, 41, 82, 35, 82, 28, 80, 80, 68, 40, 27, 43, 80, 31, 89, 83, 24. Make

(a) a frequency table and (b) a frequency polygon. (c) Make a grouped frequency table using intervals of 20-29, 30-39, 40-49, 50-59, 60-69, 7079, 80-89. Based on the...

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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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...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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...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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...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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...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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...Download Share Add to Flag Embed Views: 292 Category: Education License: All Rights Reserved Presentation Description No description available. Comments Presentation Transcript Quality Associates : Case 1 Quality Associates Introduction : Introduction It is a case of a consulting firm which consults its clients regarding statistical procedures that is used to control the production process. In this case, Quality Associates has taken example with random sample size 30 of 4 samples i.e. 120 out of 800 given observations to explain the quality control process. Hypothesis : Hypothesis H0 : µ = 12 Ha : µ ≠ 12 Level of Significance = 0.01 Z test : Z test z = Z values : Z values Test statistic (z value) for all the samples P value : P value P values (2*(1-z score))for all the samples Rejection of null hypothesis : Rejection of null hypothesis Rejection rule for two tailed test using p-value approach Reject H0 if p-value ≤ α Standard Deviation : Standard Deviation Computed standard deviation for each of the samples Quality Associates utttsav Download Share Add to Flag Embed Views: 292 Category: Education License: All Rights Reserved Presentation Description No description available. Comments Presentation Transcript Quality Associates : Case 1 Quality Associates Introduction : Introduction It is a case of a consulting firm which consults its clients......

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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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