standard deviation = square root of variance = sqrt(846) = 29.086 4. If we have the following data 34‚ 38‚ 22‚ 21‚ 29‚ 37‚ 40‚ 41‚ 22‚ 20‚ 49‚ 47‚ 20‚ 31‚ 34‚ 66 Draw a stem and leaf. Discuss the shape of the distribution. Solution: 2 3 4 5 6 | | | | | 219200 48714 0197 6 This distribution is right skewed (positively skewed) because the “tail” extends to the right. 5. What type of relationship is shown by this scatter plot? 45 40 35 30 25 20 15 10 5 0 0 5 10 15 20 Solution: Weak positive linear
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goal of the distribution of income is to achieve economic equality‚ which is to give every citizen the opportunity of earning a decent living. However‚ our current system’s inability to better allocate the resources we have at our disposal has widened the gap between the wealthy and the poor especially during the past 20 years. The primary benefit of the distribution of income is to transfer wealth‚ with the help of the government‚ to those who are less fortunate. The current distribution of income
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Normal Distribution:- A continuous random variable X is a normal distribution with the parameters mean and variance then the probability function can be written as f(x) = - < x < ‚ - < μ < ‚ σ > 0. When σ2 = 1‚ μ = 0 is called as standard normal. Normal distribution problems and solutions – Formulas: X < μ = 0.5 – Z X > μ = 0.5 + Z X = μ = 0.5 where‚ μ = mean σ = standard deviation X = normal random variable Normal Distribution Problems and Solutions – Example
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25‚ 28 26‚ 28‚ 26‚ 28‚ 31‚ 30‚ 26‚ 26 the information is to be organized into a frequency distribution. A. How many classes would you recommend? b. What class interval would you suggest? C .what lower limit would you recommend for the first class? d. organize the information into a frequency distribution and determine the relative frequency distribution. e. comment on the shape of the distribution. 15. Molly’s Candle Shop has several retail stores in the coastal areas of North and South
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solve k = 20.275 d) P ( 17 < X < 21) P ( (17 -18)/2.5 < Z < ( 21-18)/2.5) P ( -0.4 < Z < 1.2) = 0.8849 – 0.3446 = 0.5403 ( 4 decimal places) 4. In a sample of 25 observations from a Normal Distribution with mean 98.6 and standard deviation 17.2‚ find: Ans: a) n = 25‚ [pic] = ( = 98.6‚ [pic] = /n = 17.2/(25 = 3.44 [pic]( N
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POWER: A capacity that A has to influence the behaviour of B so that B acts in accordance with A’s wishes. DEPENDENCY: B’s relationship to A when A possesses something that B requires. BASES OF POWER: Formal Power: Is established by an individual’s position in an organisation; conveys the ability to coerce or reward‚ from formal authority‚ or from control of information 1. Coercive Power • A power base dependent on fear 2. Reward Power • Compliance achieved based on the ability to distribute
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The Poisson distribution is a discrete distribution. It is often used as a model for the number of events (such as the number of telephone calls at a business‚ number of customers in waiting lines‚ number of defects in a given surface area‚ airplane arrivals‚ or the number of accidents at an intersection) in a specific time period. It is also useful in ecological studies‚ e.g.‚ to model the number of prairie dogs found in a square mile of prairie. The major difference between Poisson and Binomial
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Mathematics): Survival distributions Age-at-death random variable T0 – age-at-death (lifetime for newborn) random variable To completely determine the distribution of T0 ‚ we may use (for t ≥ 0)‚ (1) (cumulative) distribution function: F0 (t) = Pr(T0 ≤ t) (2) survival function: s0 (t) = 1 − F0 (t) = Pr(T0 > t) (3) probability density function: f0 (t) = F0 (t) = (4) force of mortality: µ0 (t) = d F0 (t) dt f0 (t) −s0 (t) = 1 − F0 (t) s0 (t) Requirements: (1) For distribution function‚
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expected average outcome over many observations.The common symbol for the mean (also known as the expected value of X) is ‚ formally defined by Variance - The variance of a discrete random variable X measures the spread‚ or variability‚ of the distribution‚ and is defined by The standard deviation is the square root of the variance. Expectation - The expected value (or mean) of X‚ where X is a discrete random variable‚ is a weighted average of the possible values that X can take‚ each value
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Channels of Distribution In the uncertain fluctuating market of today‚ it is essential for a company to hold on and face those uncertainties in order to survive. Consumers can be an aid for a company’s survival‚ thereby it is essential for consumers to get the goods of a company whenever and however they need them. Here is where distribution channels come in and give hand. "Channels of distribution are the different paths that goods passed through in moving from the producer to the consumer"‚ (Meyer
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