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    Course Work

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    Question 1: We would have the work on the data set phones.sav. Therefore‚ we hoped to glance at the information of the data at initial. After the reading‚ the data set consisted of the following 12 variables that all relates to the year 2010. They were shown in the variable name and the description in the below Table 1.001. Table 1.001. The data set of phones.sav for year 2010 Variable name cell_subs fixed_line_subs GDP_percap pop_total pop_15_24 pop_15-59 pop_60plus area urbfrac comped tert_enrol

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    .................... 12 3.4 Continuous Data Histogram ................................................................................. 13 NORMAL DISTRIBUTION ................................................. 15 4.1 Properties of the Normal Distribution ............................................................. 15 4.2 Estimating Probabilities Using Normal Distribution ..................................... 16 4.3 Calculating Parts Per Million

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    any child. Baby does not have that feeling of being loved; therefore‚ she finds comfort in the fact that she was once loved. The doll is also representative of her current state of mind. Such as her wishes to be normal: have normal friends‚ normal parents‚ normal family; a normal life. When Jules destroys Baby’s rag doll out of anger‚ it is symbolic of a lost childhood. Her last reminder of the love her mother had for her had been torn away. Baby says‚ “Now I was nothing‚ a real nobody (O’Neill

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    Notes 6

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    Distribution !              for  a ≤ x ≤ b f(x) = !!! 0                        elsewhere !!! (!!!)! E(x) = ! ‚ Var(x) = ! Normal Probability Distribution Most important continuous probability distribution Many applications: heights‚ weights‚ rainfall‚ test scores Used extensively in statistical inference Shape of normal distribution is bell-shaped Characteristics: 1. All normal distributions differentiated by µμ and σ 2. Highest point is µμ (also median and mode) 3. Mean can be any value (negative

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    CHAPTER 1 : INTRODUCTION 1.1 Study Background Egg white foam is a type of foam (a colloid in which a gas is dispersed or spread throughout a liquid) used in meringues‚ soufflés‚ and angel food cake to make them light and porous (airy). To prepare egg white foam‚ egg whites are initially beaten (with a wire wisk or electric mixer or hand mixing) until they become frothy. Sugar and tartar cream can be added as a booster in order to get the maximum volume of egg foam.The temperature of the white

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    turns it into a marvelous still moment in time‚ still managing to show the great energy and power involved in the tense fight. The crowd seems to be very focused on the fight yet still disorganized and uneven‚ giving this piece a great depiction of a normal boxing match showing an unbalanced scene which helps this painting look more realistic. Bellows directs the viewer’s attention to the boxing match using the two boxers and the referee as the most prominent objects of the painting‚ to express the suspenseful

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    Coefficient of Friction

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    moving. The friction force is proportional to the normal force exerted by the surface on the body. The force’s relationship can be viewed by using the coefficient of kinetic friction‚ μk‚ in f=μkn‚ where f is the magnitude of the force of the friction‚ and n is the magnitude of the normal force. If the surface is flat‚ and horizontal‚ the normal force is equal to the weight of the object‚ due to the fact that because there is no acceleration in the normal direction‚ there is no net component in the opposite

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    How to run

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    EXERCISE MEAN‚ STANDARD DEVIATION‚ AND 95% AND 99% OF THE NORMAL CURVE STATISTICAL TECHNIQUE IN REVIEW Mean (X) is a measure of central tendency and is the sum of the raw scores divided by the number of scores being summed. Standard deviation (SD) is calculated to measure dispersion or the spread of scores from the mean (Burns & Grove‚ 2007). The larger the value of the standard deviation for study variables‚ the greater the dispersion or variability of the scores for the variable in a

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    Statistics

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    Bar Graphs 4 Stem and Leaf plots 4 Box Plots 4 Describing Bivariate Data 4 Scatterplots 4 Pearson’s Correlation 4 Spearman’s Rho 4 Probability 4 Binomial Distribution 4 Assumptions: 5 Subjective Probability 5 Normal Distribution 5 Standard Normal Distribution 5 Sampling Distribution 5 Standard Error of Statistic 5 Central Limit Theorem 5 Area under the Sampling Distribution of the Mean 6 Sampling Distribution‚ Difference between Independent means 6 Sampling Distribution

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    Proof of Black Scholes

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    Mean of a log normal random variable: Theorem 1: Suppose Y = ln X is a normal distribution with mean m and variance v‚ then X has mean exp( m + v /2 ) Proof: The density function of Y= ln X Therefore the density function of X is given by Using the change of variable x = exp(y)‚ dx = exp(y) dy‚ We have = Note that the integral inside is just the density function of a normal random variable with mean (m-v) and variance v. By definition‚ the integral evaluates to be 1. Proof of Black Scholes

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