...Wealth has something in relation to the Bible and God has established many principles regarding it. Believers must be committed and solidly rooted about what Bible, the Holy Word of God, has to say about worldly-goods. A comprehensive look at the relevant biblical passages quickly reveals that a biblical view of wealth is complex. In fact, Scripture teaches three basic principles about wealth. First, wealth itself s not condemned. Exempli gratia, we read in Genesis 13:2 that Abraham had great wealth. Also, in Deuteronomy, Proverbs and Ecclesiastes, wealth is seen as evidences of God's blessings. But even though wealth might be an evidence of God's blessings, believers are not to trust in it. Second, those who are blessed with worldly goods are not to consider themselves above others. 1 Timothy states that, "Charge them that are rich in this world, that they may be not high-minded, nor trust in uncertain riches, but in the living God, who giveth us richly all things to enjoy." Third, believers should be concerned about the effect wealth can have in their lives. Wealthy believers may no longer look to God for their provision because they can meet their basic needs. We read in Ecclesiastes 2 and 3 that people who are wealthy cannot really enjoy their wealth. The Bible doesn't really condemn those who are wealthy. But it does warn us that if God blesses us with wealth, we must keep our priorities straight and guard against the seductive effects of...
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...Belonging through relationships Meaning: A sense of belonging can be forstered through relationships this may be strengthened or broken down. Quote: Rosiland and Celia "To you I give myself for i am yours" 5.4.101 Conversation between rosiland and celia are witty and help us to understanf their friendship as close- as they banter between each other- we seee values and ideas to the society they belong to. Some characters choose not to Belong Meaning: Where most people choose to belong to a place or a person, some people choose not to belong at all. Quote: Jacques to Duke Senior "So to your pleasures; i am for other than for dancing measures" Jacques refuses Dukes invite to stay with him and his men and chooses to leave to go find the self-exiled Duke frederick. Jacques is seen to belong to himself rather than anything else. Belonging to a society or place Meaning: A person that finds pleasure or enjoyment in where they are rather than who they are with. Shown in As You Like It as a bad lifestyle. Technique: Shakespeare shows his discomfort to this lifestyle. This is shown through the murderous intentions of Duke Frederick and Oliver, who at first find their belonging to the court, until they are changed in the Forest of Ardern. Belonging to family Meaning: Where someone feels a sense of attachment to someone due to a family connection. Example: When Oliver is about to be attacked by a lion, Orlando his brother saves him, even though he knew Oliver had been sent...
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...what they can afford to buy; or even what they think they can afford to buy. With the economy being where it is right now, most people are also looking at the benefits that the car may offer, such as having low gas mileage. The hypothesis test will determine the percentage of imported cars sold at the dealership. In the conclusion, the hypothesis will either be accepted or rejected after determining the actual probability. The level of significance to be used for this calculation is .05 or 95% confidence level. Numerical Hypothesis X1: Selling price in dollars X2: Selling price in thousands of dollars X3: Age of buyer X4: 0=Domestic, 1=Imported 80 Autos Sold Ho- p= .5 (The true hypothesis should be that out of the 80 cars that were sold, 40 of them should be imported cars.) Ha- p < .5 or p > .5 (The actual statement states that out of the 80 cars sold, the number of imported cars will either be less than 40 or more than 40.) Verbal Hypothesis The percentage of imported cars sold at the Whitner Autoplex dealership should be 50%. Since the dealership carries both imported cars and domestic cars, the probability of the number of cars sold should be even, 50% imported -50% domestic. In the conclusion this hypothesis will be accepted or rejected. We tested the Autoplex data to determine the 90% and 95% chance that the cars sold on the lot are...
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...The Hedonist Perspective - Ursa Minor Beta Eroticon To live the ‘good life’- meaning to live a life of satisfaction in our everyday lives, one must compel to live and practice a life of pleasure. Living a life of pleasure refers to the actions, and thoughts, one must take in order for that fulfillment to be reached. The attainment of pleasure depends on the individual’s perception of what it means to feel pleasured. For example, one individual may be pleasured by the action of collecting comic books, while another individual may be pleasured by tearing apart comic books. In this case, it is to do whatever one must feel comfortable doing in order to reach the final end. The ultimate end is pleasure. The best form of pleasure to be practiced is to be peaceful, and negotiable to whatever the action the individual may take on. This practice is beneficial to move further away from negative forms of pain, and instead enhance all sectors of life to the best form it can be. Nature has placed species all around the universe under two sectors of governance – Pain and Pleasure. Pain inflicts negative unpleasant experiences and feelings of guilt, remorse, aches, and discomfort. Pleasure inflicts delight, satisfaction, enjoyment, and elation. Virtue allows us to be free from forms of pain, and disturbing events. Practising the pleasure sector governs our perception of life in the most positive format. We are able to distinguish our morals by what gives us the most pleasure in what we do...
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...de 0 a n * Para encontrar cuantas maneras hay de seleccionar x objetos entre n objetos se utiliza la regla de las combinaciones. * Para encontrar probabilidades: X≥ 3 = prob de 4 +3 x≤3 = prob de 2+3 x> 3 = prob de 4 x< 3= prob de 0+1+2 * La forma de probabilidad binomial depende de los valores n y p, siempre que p=0.5 la distribución binomial es simétrica, sin importar que tan grande o pequeña sea n. cuando es diferente de 0.5 es asimétrica. * 5.32 Cual es el significado del valor esperado de una distribución de probabilidad? R/: La media de una distribución de probabilidad es el valor esperado. Para calcularlo se multiplica cada resultado posible de x por su probabilidad correspondiente y luego se suman los productos. 5.33 Cuales son las cuatro propiedades que se requieren de una situación para utilizar la distribución binomial? R/:La distribución binomial se utiliza cuando la variable aleatoria es el numero de éxitos en una muestra, compuesta por n observaciones. Las propiedades son: * La muestra debe tener un numero fijo de observaciones n * Cada observación se clasifica en éxito (P) o fracaso (1-P) * La probabilidad de que una observación se clasifique como exitosa es constante de una observación a otra, al igual que la probabilidad de que sea un fracaso * El resultado de cualquier observación es independiente de cualquier otra. 5.34 Cuales son las cuatro propiedades que se requieren de una situación para utilizar...
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...variables such as marital, eservice, plusservice and totalservice we use the log-rank test of equality across strata which is a non-parametric test. For the continuous variables such as age, address, income, education, employment, and reside we use a univariate Cox proportional hazard regression which is a semi-parametric model. Univariate analysis We consider the Chi-squared test for age, address, income, education, and employ. All the variables have p-values of 0.0000 thus age, address, income, education, and employ are the potential candidate for the final model since the p-value is less than our cut-off value of 0.2. But we get different result in case of reside. We consider the Chi-squared test for reside which has a p-value of 0.5413 thus reside is not a potential candidate for the final model since the p-value is more than our cut-off value of 0.2. The log-rank test of equality across strata for the predictor marital has a p-value of 0.0136, thus marital will be included as a potential candidate for the final model because this p-value is still less than our cut-off of 0.2. From the graph (exhibit 1), we see that the survival function for each group of married or unmarried people are not perfectly parallel but separate except at the very beginning and at the very end. [pic] [pic] Exhibit 1: Kaplan-Meier Survival estimates for marital Exhibit 2:...
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...A Generation of Young Christians 1. We are always right and we never accept correction..A corrector is seen as an enemy 2. We love to sing in church, but do not read our bibles at home 3. We are full of lust, sensuality and emotions and we call it love 4. we want to have wonderful marriages, but by the time we are 25years we've spent almost ten years in relationships already. Sometimes we may have had more boy lovers and girl lovers than even our parents. 5. Sexual activities are now part of our relationships calling it romance 6. we want to be rich in life, meanwhile we spent all our finances on the latest ipads, iphone, galaxies, htcs, laptops, cameras etc which in many cases we use less than 30% of their functions 7. We do not pay our tithes and offerings claiming we are students 8. We say we are christian women but dress like hollywood stars and we call it fashion 9. We love pleasures rather than God 10. In church you will see us with our hands lifted up singing slow songs which we call worship but on our phones in our pockets, you will see pics of naked and half naked women, hip hop, hip life and we have a nice way of justifying it. 11. We are hardly convicted when we go to church because our hearts have been hardened by the deceitfulness of sin and pride...etc etc etc But God forsaw this and warned us in 2Tim. 3.. That in the last days men and women will be lovers of themselves, lovers of money, boasters, proud, blasphemers, disobedient...
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...A high school principal wanted to know if the racial makeup of her teachers mirrored that of the student body. The student body broke down into 47% White, 28% Latino, 15% African American, and 10% other. Of the 65 teachers, 42 were White, 4 were Latino, 15 were African American, and 4 were Other. Do these results suggest that the racial makeup of the faculty members is different from that of the students? (Use the .05 significance level.) Use the five steps of hypothesis testing and explain your findings. Since the teachers are given in numbers and the students in percentage therefore we will write both in percentage. | |White |Latino |Af.American |Other |Total | |% of students |47 |28 |15 |10 |100 | |% of faculty |64.6 |6.15 |23.1 |6.15 |100 | |Total |111.6 |34.15 |38.1 |16.15 |200 | Step1- H0: The racial makeup of faculty members is independent of that of the students. H1: The racial makeup of faculty members is same as that of the students. Step2- Level of significance as stated in the problem alpha=0.05 Step3- For this problem we will be using Chi-Square test. Step4- [pic] Degrees of freedom=1x2=2 ...
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...dexterity and anxiety. Higher the dexterity of a person, lower is her anxiety. This is only to be expected because more skills a person has, more confident she is and therefore less prone to being anxious. (c) R = -0.9800 and R^2 = 0.9603 We see that R = -0.98, which is close to -1, indicating a high degree of negative correlation between dexterity and anxiety. R^2 = 0.9603, which implies that 96.03% of the variation in anxiety can be explained by the variation in dexterity. (d) Hypothesis Testing: H0: There is no correlation between the dexterity score and the anxiety score, that is, β = 0 Ha: The dexterity score and anxiety score are correlated, that is, β ≠ 0. From the Regression output, we see that the p-...
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... the r value is not significant since it’s associated p-value = 0.424 > 0.05 which is the level of significance. 2.Consider r = 1.00 and r = −1.00. Which r value is stronger? Provide a rationale for your answer. Answer: The r values have similar perfect strength. The positive r value shows a positive relationship between the variables, which means as one variable increases so does the other. The negative r values shows a negative relationship, which means as one variable increases the other decreases. 3.Describe the direction of the relationship between the Hamstring strength index 60°/s and the Shuttle run test. Answer: The r value in this case is negative. So as Hamstring strength index 60°/s increases the Shuttle run test decreases, and vice versa. 4.Without using numbers, describe the relationship between the Hamstring strength index 120°/s and the Triple hop index. Answer:There exists a moderate positive relationship between Hamstring strength index 120°/s and the Triple hop index. This means as Hamstring strength index 120°/sincreases, Triple hop index increases. Likewise as Hamstring strength index 120°/s decreases, Triple hop index decreases. 5.Which variable has the weakest relationship with the Quadriceps strength index 120°/s? Provide a rationale for your answer. Answer:The Shuttle run test has the weakest relationship with Quadriceps strength index120°/s. That is because the absolute value of the r value is less than all the others, and the p value is greater than all others...
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...Explain the difference between a left-tailed, two-tailed, and right-tailed test. When would you choose a two-tailed test? How might you tell the direction of the test by looking at a pair of hypothesis? How might you tell which direction (or no direction) to make the hypothesis by looking at the problem statement (research question)? The direction of the test is indicated by the alternate Hypotheses H1. < indicates a left tailed test and > indicates a right tailed test. One would choose a two tailed test when the direction of < or > does not matter to the researcher. Two tailed tests are indicated by =. One would also choose a two tailed test if the rejection of the two tailed test guarantees a rejection of the left or right tailed test. I think one can tell which direction the hypothesis should be by the way the research question is worded. Certain words can mean less than or greater than;: or equal to or not equal to; or greater than or equal to some number. One just needs to read the hypothesis carefully to make sure he or she is conducting the test in the correct direction or the test will be done wrong. An example of this would be where the average means of monthly wages for a population area is $1,800 and someone questions this saying they believe it is higher for the particular area. So the hypothesis for this particular scenario would be written out as: H0 : µ > 1,800 H1 : µ ≤ 1,800 Please try to respond to this question by at least...
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...After I read Mill’s notion of higher and lower pleasures, I changed the view of my opinion about higher and lower pleasures. Before that, I thought we just need happiness, and then it will be ok. I never think about what kind of pleasures are higher or lower. Through Mill’s view, it’s really difficult to define higher and lower pleasure. But at least, Mill equates happiness with pleasure, and not all pleasures have equal value; higher pleasures of the mind are better than lower pleasures of the body. For human beings, first thing is to seek the most and best food, drink, sleep, sex and so on. This can satisfy people’s lower pleasure. However, people also need higher pleasures. So what are higher pleasures? It mostly focuses on spiritual happiness. Of course, after people’s lower pleasures been satisfied, then people can started to seek higher pleasures. Try to think about it, if people cannot feed themselves, who will try to learn the science. So, reading a good book, seeing a good play or other edifying pleasures would be far superior and would supersede food, drink, sleep, sex etc. When people who are tolerably fortunate in their outward lot find life unhappy, it usually is because they lack altruism or are deficient in mental cultivation. Those who cherish a fellow-feeling for others will always retain a pleasurable interest in life; and a cultivated mind finds inexhaustible interest in all that surrounds it--nature, art, poetry, history, the past, present and future of mankind...
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...(c) Hypothesis test: 1) For TXRH LOGR: H0: µLOGR = 0 HA: µLOGR ≠ 0 α=0.05 t~t2012, 0.025 (n = 2013) tj0 = (0.000519-0) / (0.024138/√2013) = 0.96, t2012, 0.025 = 1.96 Since tj0 < t2012, 0.025, we accept H0 at 5% significance level, otherwise we reject H0. 2) For HPQ LOGR: H0: µLOGR = 0 HA: µLOGR ≠ 0 α=0.05 t~t2012, 0.025 (n = 2013) tj0 = (0.000039-0) / (0.021745/√2013) = 0.08, t2012, 0.025 = 1.96 Since tj0 < t2012, 0.025, we accept H0 at 5% significance level, otherwise we reject H0. 3) For QQQ LOGR: H0: µLOGR = 0 HA: µLOGR ≠ 0 α=0.05 t~t2012, 0.025 (n = 2013) tj0 = (0.000467-0) / (0.014261/√2013) = 1.47, t2012, 0.025 = 1.96 Since tj0 < t2012, 0.025, we accept H0 at 5% significance level, otherwise we reject H0. (d) Hypothesis test: 1) For TXRH LOGR: H0: SLOGR = 0 HA: SLOGR ≠ 0 α=0.05 t~t2012, 0.025 (n = 2013) tj0 = 0.482322 / √ (6/2013) = 8.83, t2012, 0.025 = 1.96 Since tj0 > t2012, 0.025, we reject H0 at 5% significance level, otherwise we accept H0. 2) For HPQ LOGR: H0: SLOGR = 0 HA: SLOGR ≠ 0 α=0.05 t~t2012, 0.025 (n = 2013) tj0 = -0.544118 / √ (6/2013) = -9.97, t2012, 0.025 = 1.96 Since ǀtj0ǀ > t2012, 0.025, we reject H0 at 5% significance level, otherwise we accept H0. 3) For QQQ LOGR: H0: SLOGR = 0 HA: SLOGR ≠ 0 α=0.05 t~t2012, 0.025 (n = 2013) tj0 = -0.092710 / √ (6/2013) = -1.70, t2012, 0.025 = 1.96 Since ǀtj0ǀ < t2012, 0.025, we accept H0 at 5% significance level, otherwise we reject H0. (e) Hypothesis test: 1) For TXRH LOGR: H0: KLOGR -...
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...or 2.074 = = .43, p-value = .6703. There is not enough evidence to infer that the population means differ. b Equal-variances test statistic Rejection region: –2.074 or 2.074 = = .04, p-value = .9716. There is not enough evidence to infer that the population means differ. c The value of the test statistic decreases and the p-value increases. d Equal-variances test statistic Rejection region: –1.960 or 1.960 = = 1.53, p-value = .1282. There is not enough evidence to infer that the population means differ. e The value of the test statistic increases and the p-value decreases. f Rejection region: –2.074 or 2.074 = = .72, p-value = .4796. There is not enough evidence to infer that the population means differ. g The value of the test statistic increases and the p-value decreases. 13.7 a Unequal-variances estimator = 64.8 (rounded to 65, approximated by ) = (63 – 60) 1.667 = 3 4.59 b Unequal-variances estimator = 63.1 (rounded to 63, approximated by ) = (63 – 60) 1.671 = 3 10.38 c The interval widens. d Unequal-variances estimator = 131 (approximated by ) = (63 – 60) 1.656 = 3 3.22 e The interval narrows. 13.8 = 0 0 a Unequal-variances test statistic = 200.4 (rounded to 200) Rejection region: = = .62, p-value = .2689. There is not enough evidence to infer that is greater than . b Unequal-variances test statistic = 223.1 (rounded to 223) Rejection region: = = 2.46, p-value = .0074. There is...
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...tanto contribuye cada variable a la explicación del comportamiento de la variable de respuesta, se buscará establecer un modelo de regresión lineal múltiple que incluya las variables mencionadas y que muestre la contribución de cada una al nivel de sílice con el propósito de permitir o facilitar su manipulación para lograr la respuesta esperada. Para determinar el mejor modelo lineal de entre todas las posibles combinaciones entre variables, se estableció primero un modelo que las incluía todas. Del ANOVA de este modelo, se analizó la R2a ya que resulta ser un buen indicador en modelos de más de una variable ya que penaliza la adición de las mismas en caso de ser inútiles, el valor F, los coeficientes de las regresoras y sus valores t y P. La R2a presentó un valor muy bajo de 0.635945343, lo que representa el 63.6% de la cantidad de variación explicada por la regresión. Sin embargo, a partir de la misma, comparamos el valor F proporcionado por el ANOVA vs. el valor F de tablas (en base a los parámetros del modelo). De esto se obtuvo lo siguiente: F= 16.37219 > F0.05,5,39 = 2.458, por lo cual se rechaza la hipótesis nula Ho: β1 = β2 = β3 = β4 = β5 = 0 y se acepta la hipótesis...
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