A lecithin/sphingomyelin (L/S) ratio has been ordered by a p…
Questions
A lecithin/sphingоmyelin (L/S) rаtiо hаs been оrdered by а pregnant woman's obstetrician. Which of the following data will the nurse learn from this test?
Spelling, punctuаtiоn, аnd аccent mark cоunt tоward grading. Misspelled, wrong tense, wrong form of verbal conjugation, article, or preposition (- full points worth). Missing accents from the words you have been exposed to during the chapter, punctuation--periods, capital letters, upside-down exclamation or question marks--If needed (-1/4 points). Accent Marks Please write me a short message, in parenthesis, next to the word that needs it, for instance: You need to write ¡Mi mamá comprará el juguete mañana para Iván! You will write it like (upside-down exclamation mark) Mi mama (accent on the 2nd a) comprara (accent on the second a) el juguete manana (tilde over the 1st n) para Ivan (accent on a)! Notice that when there is more than one repeated vowel/consonant, I used more details on which vowel/consonant the accent mark was placed--mamá, mañana, etc. Unlike the name "Ivan" which has one accentuated vowel. Directions: You have been introduced to the acronym PLACES. You learned that each letter stands for a meaning to a grammatical rule to use with "Estar". Please explain the grammatical rule per acronym letter and give Spanish examples with each rule. (The grammatical rule answers can be written in English but your sentence examples must be in Spanish.) Modelo: The letter A, in PLACES, stands for "Action Now". Spanish sentence: Vosotros estáis comiendo ahora . Why I used my Spanish sentence with this acronym: I used the letter A for "action now" because the word "estáis comiendo" refers to an action that is happening at the time of speech (things that are happening right now--present progressive). 1 point for a complete Spanish sentence. 1 point for a correct complete description of why you used your Spanish sentence with a specific acronym. The letter P, in PLACES: Spanish Sentence ________ Why I used my Spanish sentence with this acronym: __________ The letter L, in PLACES: Spanish Sentence ________ Why I used my Spanish sentence with this acronym: __________ The letter A, in PLACES: Spanish sentence: Vosotros estáis comiendo ahora . Why I used my Spanish sentence with this acronym: I used the letter A for "action now" because the word "estáis comiendo" refers to an action that is happening at the time of speech (things that are happening right now--present progressive). The letter C, in PLACES: Spanish Sentence ________ Why I used my Spanish sentence with this acronym: __________ The letter E, in PLACES: Spanish Sentence ________ Why I used my Spanish sentence with this acronym: __________ The letter S, in PLACES: Spanish Sentence ________ Why I used my Spanish sentence with this acronym: __________ Please write the task number followed by your answer. Do not do #3, this is already done.
Questiоn 2: Multiple lineаr regressiоn (30 pоints) Use trаinDаta dataset for parts (a)-(d) and use the testData for part (e). a) Fit a regression model predicting salary using the following predictors: 'education_level', 'has_certification', and 'years_experience'. Call it model1. Display the summary. Interpret the coefficient of 'has_certification'. State any assumptions while interpreting the coefficient. (3 points) b) Refit model1 and add an interaction term education_level * has_certification. Call it model2. Display the summary. (2 points)i) Is the interaction term significant at a level of 0.01? (1 point)ii) Interpret the coefficient of the interaction term education_levelMasters:has_certification1. State any assumptions while interpreting the coefficient. Note: Interpret the coefficient irrespective of its statistical significance. (3 points)iii) Calculate the Variance Inflation Factor (VIF) for each predictor group in your model, where each group represents all the dummy variables created for a given categorical variable (such as all the dummies for education level), or for an interaction term (such as all dummies in educationlevel × hascertification). Report the overall VIF for each predictor group, not just for individual dummy variables. Based on these VIF values, which predictors show potential multicollinearity issues? Explain why the interaction terms have higher VIFs than the main effects. (3 points) c) Based on your model in Q2a, predict the expected salary of a Bootcamp graduate with 3 years of experience and a certification. Explain your results. (3 points) d) Fit a regression model predicting salary using num_internships, years_experience, and education_level. Call it model3. Display the summary. (2 points)i) Based on your model (model3), how much higher would you expect the salary to be for a candidate with 2 internships compared to none (holding other factors constant)? (3 points) e) Using the testData and models model1 (2a), model2(2b), model3 (2d), predict 'starting_salary_usd' for each row in testData. Calculate the precision measure for each model's predictions. (6 points)i) Which model performed the best according to the value of precision measure? (2 points)ii) Interpret the precision measure value of model1 in the context of prediction accuracy. (2 points)