mind that a statistic is only worthwhile when it satisfies the assumptions on the test. Knowing whether the assumptions are met is dependent on the competence of the person running the test. Just because two things seem to have a relationship‚ could it have been by pure chance? It cannot be determined by causation and effect. The two variables have no effect on each other at all. Chapter 9 – How to Statisticulate Statisticulate is the process of misleading people using statistics. It is also
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Pakistan International School Riyadh Class XII 1. How many possible permutations can be formed from the word ‘statistics’? 2. In how many ways can a team of 11 players be chosen from a total of 16 players? 3. State multiplicative theorem of probability for dependent events. 4. An aptitude test with 4 options. If a student marks the options of the questions randomly and independently‚ then find the probability of being correct to 4 questions. 5. A can solve 75% questions in a
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crime statistics fail to provide an accurate portrayal of the level of crime in society? Crime is ‘an action or omission which constitutes an offence which is punishable by law’ (Oxford Dictionary). Criminal behaviour is an issue in society today. Crime statistics providing evidence is vastly important because the government or police forces can look at the level of crime‚ identify if is increasing or decreasing; remedy the situation using prevention tactics. Consequently‚ the statistics are influenced
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The Columbian Exchange Statistics By the Numbers Estimated population of Europe in 1492: about 60 million Estimated population of the Americas in 1492: 40-100 million Estimated population of Europe in 1800: 150 million Estimated population of the Americas in 1800: 25 million (the vast majority of whom were of European or African descent) Major domesticated animals in the New World in 1492: dog‚ llama Major domesticated animals in the Old World in 1492: horse‚ cow‚ pig‚ sheep‚ goat‚ chicken
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Level of Significance (alpha) 0.010 0.010 0.010 0.010 Critical Value (lower tail) -2.576 -2.576 -2.576 -2.576 Critical Value (upper tail) 2.576 2.576 2.576 2.576 Hypothesized value 12 12 12 12 Standard Error 0.040 0.040 0.038 0.038 Test Statistic -1.027 0.713 -2.935 2.161 p-value 0.304 0.476 0.003 0.031 Only sample 3 leads to the rejection of the hypothesis H0: µ = 12. Thus‚ corrective action is warranted for sample 3. The other samples indicate H0 cannot be rejected and thus from all
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Descriptive Statistics is used when describing certain aspects of an immediate group within the population. For example‚ we may want to describe a math class and compare it to a class of science. Things that we may want to use for comparison would be age‚ gender‚ and even math skills. Descriptive statistics would allow us to analyze all those different areas and provide a comparison to view similarities‚ differences and ratios. Before any study is to be observed certain factors would have to be ascertained
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Research‚ Statistics‚ and Psychology PSY 315 Amber Lupo November 8‚ 2010 Amber Nelson “The definition of scientific method is a method of research in which a hypothesis is tested by means of a carefully documented control experiment that can be repeated by any other researcher” (yourdictionary.com‚ 2010.) “Research is the scholarly or scientific investigation or inquiry” (American Heritage Dictionary‚ 2000.) Primary and secondary data are dependent to each other‚ but also completely
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Population variance = σ2 = Σ ( Xi - μ )2 / N * Variance of population proportion = σP2 = PQ / n * Standardized score = Z = (X - μ) / σ * Population correlation coefficient = ρ = [ 1 / N ] * Σ { [ (Xi - μX) / σx ] * [ (Yi - μY) / σy ] } Statistics Unless otherwise noted‚ these formulas assume simple random sampling. * Sample mean = x = ( Σ xi ) / n * Sample standard deviation = s = sqrt [ Σ ( xi - x )2 / ( n - 1 ) ] * Sample variance = s2 = Σ ( xi - x )2 / ( n - 1 ) * Variance
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were randomly and independently chosen from the populations‚ population distributions are normal for each group; and population variances are equal for all groups. The assumptions of ANOVA are identical to the t-test and the calculated statistic is called an F-value which has a probability value associated with it. As with the t-test‚ if our probability value is less than 0.05 we reject our null hypothesis (in this case that there is no difference among the treatment groups). This p-value
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independent observations by the number of observations in the group that represent one of two outcomes. For example‚ the proportion of individuals in a random sample who support one of two political candidates fits this description. In this case‚ the statistic is thecount X of voters who support the candidate divided by the total number of individuals in the group n. This provides an estimate of the parameter p‚ the proportion of individuals who support the candidate in the entire population. The binomial
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