The objective of this paper is to analyze the process identified in Week Ones project of examining a daily process that may requirement improvement, apply statistical process control, determine the effect of any seasonal factors, and apply confidence intervals to the data points collected over the last four weeks. Process Description The process from Week Ones project is ‘Making Dinner’ during the week days. The daily task of making dinner for a family takes time and commitment, if time can
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to complain that the bottles of the brand of soda produced in this company contains less than the advertised 16 ounces of product. I have pulled 30 bottles of soda and am calculating the mean, median, standard deviation, constructing a 95% confidence interval and conducting a hypothesis test to verify the claim that a bottle contains less than 16 ounces is supported. The first set of tests will consist of calculating the mean, median and standard deviation for ounces in the bottles. Below is the
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have significantly different means. This can be tested by calculating the confidence intervals of the means of the three subgroups (probability 95%) by means of Y ̅±t*s_Y ̅ . If two confidence intervals don’t have any common point, then their population means differ significantly. Otherwise there is no significant difference. I compute these confidence intervals and by plotting them it is obvious that the confidence interval for
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parts of an M&M analysis and examine a method for quality control. The parts of this project included using random sampling to gather data on the number of colored M&M candies, the sample proportion and sample mean, constructing a 95% confidence interval and testing claims of M&M candies. By the end of this report a better understanding of the methods behind packing M&M candies should be gained. Project Part 1: Sampling Method To begin the M&M analysis a random sample of three
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087 3.131 3.241 3.241 3.270 3.353 3.400 3.411 3.437 3.477 (a) Construct a 90 percent confidence interval for the true mean weight. Confidence interval =[pic]+ z*[pic] sample mean = 3.3048 = μ 3.087 + 3.131 + 3.241 + 3.241 + 3.270 + 3.353 + 3.400 + 3.411 + 3.437 + 3.477 = 33.048 / 10 = 3.3048 Std. Deviation= 0.1320 z(90) = 1.645 Sample Size= N = 10 Confidence Interval= μ + 1.645*σ = 3.3048 + 1.645*0.1320 = (3.236, 3.373) √10 √10 (b) What
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You ask your employees to measure the amount of soda there is in each bottle. A Confidence interval is a term used in inferential statistics that measures the probability that a population or sample parameter will be fall between two set values. The confidence interval can take any number of probabilities, with the most common being 95% or 99% (Investopedia.com, n.d.). To find the 95% confidence interval for the ounces in the bottles, we need to find the margin of error E. E =Z_C*(Ó/√(n)
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Number of pizzas sold last year in Malaysia | ̷̷ | | e. | Weights of newborn infants at a certain hospital | ̷̷ | | f. | Water temperature of the sauna at a health spa | | ̷̷ | 3. Classify each as nominal-level (N), ordinal-level (O), interval-level (I) or ratio-level ®. (Tick your answers in the correct category) | | N | O | I | R | a. | Ages of students enrolled in a martial arts course | ̷̷ | | | | b. | Rankings of weight lifters | | ̷̷ | | | c. | Temperature of automatic
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Multiple Choice Answer the next two questions based on the following: A water utility manager worried that demand has changed from its former 110 million gallons monthly average samples the most recent 60 months (millions of gallons/month). TEST OF MU = 110.00 VS MU NOT = 110.00 N MEAN STDEV SE MEAN T P VALUE DEMAND 60 117.70 14.42 1.86 4.14 0.0001 1. A test is conducted at the ( = 0.01 level to determine if average monthly demand now
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Assignment 6 – Data Analysis ETM 5943 10/29/2012 I have used SAS Enterprise Guide 5.1 to analyze the given data. Part 1 (Basic statistics and graphical analysis) Data: ETM_data_analysis1.xls, tab Shipping A project team is assigned a task to determine why customer complaints are increasing regarding the shipping operation. The attached data set provides several weeks of data with due dates, ship dates and the day of the week the orders shipped. Days Late is calculated from the
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Probability and statistics are two related but separate academic disciplines. Statistical analysis often uses probability distributions, and the two topics are often studied together. However, probability theory contains much that is of mostly of mathematical interest and not directly relevant to statistics. Moreover, many topics in statistics are independent of probability theory. Probability (or likelihood) is a measure or estimation of how likely it is that something will happen or that a statement
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