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Statistic paper 1 - Essay Example

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Course Date Save Time in Breakfast Cereal Selection Scope of the Work The following sections present justification of the research question, method of data collection, description and presentation of data, analysis of data, and conclusion of analysis through hypothesis test…
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How does a consumer know which one contains the lowest calorie amidst so many brands? This assignment establishes facts that will help customers navigating through the aisles in search for cereal of deserved calorie. This will be achieved by establishing a population mean of calories of 100 gram of cereals regardless of cereal brands. Should a customer plan on finding a cereal packet that contains calories lower than the mean, the customer would need more time to find it than the packet with the mean value.

Data Collection Breakfast cereal population, in this case, is different brands that are available at the website the calorie counter (“The Calorie Counter”). The data of each sample represents the published calorie value of 100 grams of breakfast cereals. Therefore, sample unit for this study is breakfast cereal, and the response unit is calorie per 100 gram. The population study reveals that General Mills, Kellog, Kraft, Malt – o- Meal, and Quaker companies are principal manufactures of the breakfast cereals (The Calorie Counter).

General Mills produces 48 brands, Kellog produces 40 brands, Kraft produces 24 brands, Malt – O – Meal produces 9 brands, and Quaker produces 44 brands. The population consists of 165 brands. The study uses samples of 30 individual breakfast cereals selected randomly from this population. The population consists of 5 strata. This study uses stratified sampling technique to collect sample data. Numbers of samples from each stratum are calculated using the formula; (Population of the stratum / entire population) x 30.

Sample size, n = 30 is determined on literature review for determining the sample size for statistical analysis (“30 Samples”). Description and Presentation of Data This research uses retrospective observational quantitative data; variables with numerical values. Quantitative data have two classes: discrete and continuous. If a variable can take values between a minimum and maximum, it is called continuous variable otherwise it is discrete. Based on the above discussion this assignment will use continuous quantitative data.

The sample data of this assignment is presented using stem and leaf, and array tables. Stem and Leaf Table. It presents data in all of its detail. It describes the range and relative frequency of each value in the set. The stem and leaf table helps determine the best grouping level for a frequency histogram. In this assignment, the each value of sample data set consists of three digits. Raw data set is rearranged in an ascending order; first two digits are considered the stem and corresponding leafs are counted for each stem.

Table 1 displays the values of the data set in the form of stem and leaf. Table 1. Stem and Leaf Data Distribution Total 31 1 1 32 0 3 2 33 2 4 2 34 0 1 35 0 2 2 36 5 1 37 0 3 3 6 8 5 38 0 1 3 3 7 7 6 39 0 1 2 3 6 6 6 40 0 9 2 41 2 5 2   Subtotal 30 Array Table. It is arranged to present data in a tabular form of columns and rows. Table 3 displays data in ascending order in an array. Data are arranged in three rows, and each row consists of 10 columns Table2. Array Form Data Distribution 1 2 3 4 5 6 7 8 9 10 311 320 323 332 334 340 350 352 365 370 373 373 376 378 380 381 383 383 387 387 390 391 392 393 396 396 400 409 412 415 Histogram.

Table 2 displays sample data in the array form. The minimum value is 311, and the maximum value is 415. The

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