Name<\/p>\n
Course<\/p>\n
Institution<\/p>\n
Part 1: Case Study<\/p>\n
Identify <\/p>\n
Potential problems in the manufacturing process<\/p>\n
Both the small, medium and large engines would be skewed to having poor performances as listed.<\/p>\n
There are also mechanisms that have led to compact, large, mid-size, small, sporty and vans. Passengers are observed to have issues with the vehicles owing to how they have been made.<\/p>\n
There are also various vehicles having issues when it comes to the MPG.<\/p>\n
The fuel tank is also observed to be having issues with the developments. This is in relation to large, medium and small tanks.<\/p>\n
Investigate these high and low measurements<\/p>\n
Manufacturer Origin Model Type Passengers Price<\/p>\n
Honda non-US Civic Small 4 12.1<\/p>\n
Geo non-US Metro Small 4 8.4<\/p>\n
Suzuki non-US Swift Small 4 8.6<\/p>\n
The price of Honda more so, the small one is affordable.<\/p>\n
Highest 10% and the lowest 10% of these measurement<\/p>\n
Q1 1.2175<\/p>\n
Q4 2.285<\/p>\n
Better ways to select the outlier values<\/p>\n
When the interquartile range is given a multiplier effect of 1.5. Then we are able to ascertain the outlier values that are present.<\/p>\n
Subtraction of 1.5 interquartile range from the 1st quarter would result in less values deemed as outliers. Hence, the numbers would be sorted from high to low. This can be visualized through a box plot.<\/p>\n
Fences can be used to introduce interquartile ranges.<\/p>\n
Statistical procedures can be used to come up with the skewed values.<\/p>\n
Reasoning and answers for distributions that are normal or skewed<\/p>\n
Their ought to be outliers in a system of which would result in the framework having a normal curve. The values cannot be the same at any given point. Thus, proving that they are correct and have a statistical element.<\/p>\n
Part 2: Box Plot<\/p>\n
Population size: 92<\/p>\n
Median: 17.6<\/p>\n
Minimum: 7.4<\/p>\n
Maximum: 47.9<\/p>\n
First quartile: 12.125<\/p>\n
Third quartile: 23.15<\/p>\n
Interquartile Range: 11.025<\/p>\n
Outliers: 47.9 40.1<\/p>\n
Weight data from the Cars data set located in the Group Project assignment<\/p>\n
Values for the 5-number summary<\/p>\n
Upper and lower fences<\/p>\n
Discuss the shape of the data outliers in your comments. <\/p>\n
References <\/p>\n","protected":false},"excerpt":{"rendered":"
Name Course Institution Part 1: Case Study Identify Potential problems in the manufacturing process Both the small, medium and large<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-35424","post","type-post","status-publish","format-standard","hentry"],"yoast_head":"\n