I need to analyze the raw data collected. and use Google Sheets, create two scatter plots:

• onecomparing the number of lbs. of laundry a household does per week with the likelihood that they would use the service.
• another comparing a customer's distance from Drip & Dry with the likelihood of them using the service.

Icneed learn how to find the line of best fit, also known as a trend line, which approximates the data on the scatterplot and the R-squared values to help explain how close the data is to the trend line.I also have to explain whether or not there are meaningful correlations within the variables for each scatterplot (pounds of laundry vs. likelihood to use the service and distance vs. likelihood to use the service.)

Portland Laundry Statistical Data GOPYOF SURVEY Greetings trorn Drip and Dry! We are thinking of opening a new laundry delivery service. We wit pick Lu your clotee, wash them, told them, iron them [ifrequeemed]: and retum them to you in clean cloth bags To ensure that this service fully meets the needs of Portland's residents, we are sending you ttis brief survey about you laLI'Icl'y needs. Thai! you I'oryour participation and look for more information about our new program soon! How far is your residence from Drip and Dry? [In mile-s]: Whatis'leaveragearmttoflaundryymnashperweenlbsj *An average load oaundry is about Tt' the. How Iltely are you to use a laundry pidcw service? (Gide one) Always Frequently Sometimes Rarely Never {5} {4i {3) {2} i1} |fyouusedalal.ryseryice,mldymexped1efoloing servioeoponsrcle'rorm Folling'Ht'l DryClea'ing'I'iN SpecialCa'e'r'iN EocFriendinashing WM 'l'l'laicywrtalringourwnrey! Welookfoma'dtoneaoppottuiestoseweymrwaslingneeds \f\f