A researcher is trying to determine whether flight arrival delays occur based off of what time of the year it is using data from the last five years. The data table shows the sum of the last five years worth of the number of flight departure delays and on time departures based off of each month of the year. The researcher's hypothesis (HA): Flight departure delays are dependent on the time of year. Null Hypothesis: Flight departure delays are unaffected by the time of year.

Conduct a two sample T-test with the following data step by step using the FIVE STEP HYPOTHESIS process.

 

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Table 2 Flight Departure Delays (2015-2019). Month Flight Departure Delays On Time Departures January 453,388 2,001,099 February 418,608 1,841,012 March 465,257 2,196,729 April 443,184 2,142,229 Мay 499,543 2,181,025 June 606,351 2,098,931 July 608,194 2,184,496 August 568,344 2,207,521 September 347,768 2,185,428 October 386,235 2,284,507 November 370,504 2,173,172 December 645,688 2,072,911 Table 2 Flight Departure Delays (2015-2019). Month Flight Departure Delays On Time Departures January 453,388 2,001,099 February 418,608 1,841,012 March 465,257 2,196,729 April 443,184 2,142,229 Мay 499,543 2,181,025 June 606,351 2,098,931 July 608,194 2,184,496 August 568,344 2,207,521 September 347,768 2,185,428 October 386,235 2,284,507 November 370,504 2,173,172 December 645,688 2,072,911

Answer rating: 100% (QA)

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