BICOL STATE COLLEGE OF APPLIED SCIENCE AND TECHNOLOGY NAGA CITY HISTORY OF STATISTICS Group 3 Members: Tricia Mae Berja Michelle Lee Desiree Basmayor Mica Rubio Gian Perucho Ivan Ricafort Ms. Donnalyn Matamorosa Dominic Bobis Teacher Alex Obligado Ancient Times (3000 BC – 27 BC) * Pictorial representation and other symbols were used for Statistics back in the days. (To record numbers of people‚ animals‚ etc.) * In Babylonia and China‚ population is
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Elementary Concepts in Statistics Overview of Elementary Concepts in Statistics. In this introduction‚ we will briefly discuss those elementary statistical concepts that provide the necessary foundations for more specialized expertise in any area of statistical data analysis. The selected topics illustrate the basic assumptions of most statistical methods and/or have been demonstrated in research to be necessary components of one’s general understanding of the "quantitative nature" of reality
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data using Descriptive Statistics | 4-6 | 2 2.1 2.2 | Estimated regression equations. Independent Variable- Annual Income. Independent Variable- Household Size | 7 8 9 | 3 | Better predictor of annual credit card charges | 10 | 4 | Independent variables- Annual income and Household size | 11 | 5 | Forecasting Annual Credit Charge | 12 | 6 | Need for other independent variables | 13 | 7 | Test the significance of the overall regression model | 14 | 8 | Test the significance of the
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better decisions when they use all available information in an effective and meaningful way. The primary role of statistics is to to provide decision makers with methods for obtaining and analyzing information to help make these decisions. Statistics is used to answer long-range planning questions‚ such as when and where to locate facilities to handle future sales. 2 Definition s Statistics is defined as the science of collecting‚ organizing‚ presenting‚ analyzing and interpreting numerical data
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are two main branches of statistics that include descriptive statistics and inferential statistics.Descriptive statistics gives numerical measures that describes the features of a given set of data. Inferential statistics on the other hand takes a sample of a given population‚ analyses the sample‚ and from it draw conclusions about the population .Malcolm.O.Asadoorian and Demetrius Kantarelis in their book: Essentials of inferential statistics argue that descriptive statistics organize ‚ summarize and
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Simply use statistics as a tool. You will be given a data. (Next year you will not be given data‚ you will gather data yoruself). 1. Data: one of the variables is dependent and other dependent. Can be multiple. Then do regression analysis. ANOVA for overall significance and Regression equation. And write based on ANOVA there is a significance or not. 2. Some comments on correlation: volume vs. horse power etc. 3. Hypothesis test of one population. I assume that the mean is etc etc. Small paragraph
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Parametric Hypothesis tests are frequently used to measure the quality of sample parameters or to test whether estimates on a given parameter are equal for two samples. Hypothesis tests are parametric tests when they assume the population follows some specific distribution (such as normal) with a set of parameters. The t-test determines whether a sample is representative of a known population or whether paired samples are likely to be from the same. This test is used for descriptive test in sensory
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WEEK FOUR DQ1 Explain the importance of random sampling. What problems/limitations could prevent a truly random sampling and how can they be prevented? Probability sampling‚ also known as random sampling‚ requires that every member of the study population have an equal opportunity to be chosen as a study subject. For each member of the population to have an equal opportunity to be chosen‚ the sampling method must select members randomly. Probability sampling allows every facet of the study population
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increase by 0.0953 billion dollars (c) Comment on the significance of model (α = 0.05) Hypotheses: H0: β1 =0 H1 : β1 ≠ 0 Decision rule: reject H0‚ if |tcalc|> |t(α/2‚ n-k-1)| Where tcrit = t (0.025‚ 98) =1.9845 Test statistic: t = = = 48.368 Decision: Reject H0 because t calc > t crit Conclusion: There is sufficient evidence to conclude that there is significant relationship between disposable personal income and PCE at 5% level of significance. (d)
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Basics of Statistics Jarkko Isotalo 30 20 10 Std. Dev = 486.32 Mean = 3553.8 N = 120.00 0 2400.0 2800.0 2600.0 3200.0 3000.0 3600.0 3400.0 4000.0 3800.0 4400.0 4200.0 4800.0 4600.0 5000.0 Birthweights of children during years 1965-69 Time to Accelerate from 0 to 60 mph (sec) 30 20 10 0 0 Horsepower 100 200 300 1 Preface These lecture notes have been used at Basics of Statistics course held in University
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