You are given data to analyze for a new chemotherapeutic to eliminate malignant tumors and must...

 

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You are given data to analyze for a new chemotherapeutic to eliminate malignant tumors and must determine if a significant relationship of any kind exists for the latest drug that was proposed. This new drug, XA98 has shown promising results across multiple repeated cross-sectional studies and now combined evidence was gathered to see if any relationships stand out among the multiple tests that were conducted in the past. The data for XA98 to combat specific cancer tumors can be found below, establish whether or not any significant relationships exist among the variables and describe how strong these relationships are; hint: think about using linear regression to establish any relationships that can be described with a simple model and pinpoint which variables are critical for understanding these relationships. Feel free to use any resources from the web or from your notes. The dataset consists of four variables, in vivo fluorescence for XA98 (photon arrival time in picoseconds); tumor size (in volume mm'); ultrasonography for XA98 (in hertz); excitation light for XA98 (in nm) vivo fluor: 123, 34, 56, 78, 29, 19, 101, 283, 98, 76 tumor_size: 23, 43, 51, 56, 72, 34, 98, 12, 34, 23 ultrasono: 34, 44, 54, 44, 34, 44, 45, 54, 67, 88 excitation: 110, 112, 114, 112, 113, 114, 224, 112, 115, 111 You are given data to analyze for a new chemotherapeutic to eliminate malignant tumors and must determine if a significant relationship of any kind exists for the latest drug that was proposed. This new drug, XA98 has shown promising results across multiple repeated cross-sectional studies and now combined evidence was gathered to see if any relationships stand out among the multiple tests that were conducted in the past. The data for XA98 to combat specific cancer tumors can be found below, establish whether or not any significant relationships exist among the variables and describe how strong these relationships are; hint: think about using linear regression to establish any relationships that can be described with a simple model and pinpoint which variables are critical for understanding these relationships. Feel free to use any resources from the web or from your notes. The dataset consists of four variables, in vivo fluorescence for XA98 (photon arrival time in picoseconds); tumor size (in volume mm'); ultrasonography for XA98 (in hertz); excitation light for XA98 (in nm) vivo fluor: 123, 34, 56, 78, 29, 19, 101, 283, 98, 76 tumor_size: 23, 43, 51, 56, 72, 34, 98, 12, 34, 23 ultrasono: 34, 44, 54, 44, 34, 44, 45, 54, 67, 88 excitation: 110, 112, 114, 112, 113, 114, 224, 112, 115, 111

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