100 Questions And Answers About Research Methods Pdf

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Last Modified: 2. Views. 2. 26. 6. . Name American Board of Family Medicine IN- TRAINING EXAMINATION TIME–4 HOURS Read the instructions on the back first. Do not break the seal until you are told to do so. Write your name in the blank at the top of the page. Record your Program Number and ABFM Number on the answer sheet, as shown in the sample on the right. Write your name, your program name, and the date on the answer sheet.

Publication or reproduction in whole or in part is strictly prohibited. A 7. 2- year- old white male develops a rapidly growing epithelial tumor just in front of his right ear. He states that it began as a firm red papule about 6 weeks ago.

It is now 1. 5 cm in diameter and has a horny plug in the center. The most likely diagnosis is A) Bowen’s disease B) basal cell carcinoma C) keratoacanthoma D) Kaposi’s sarcoma E) seborrheic keratosis 2.

An 8- year- old male is brought to the emergency department with an acute asthma attack that began 4. His mother initiated his asthma action plan when the attack began, starting oral prednisolone plus albuterol (Proventil, Ventolin) by metered- dose inhaler with a spacer every 3–4 hours.

In the emergency department the child is alert, with a respiratory rate of 3. He is audibly wheezing.

Peak flow is 4. 0% of the predicted value. Which one of the following should you do next? A) Continue the current albuterol treatment but switch to a nebulizer B) Administer high- dose albuterol via nebulizer every 2. C) Administer intravenous corticosteroids within the first hour D) Administer magnesium sulfate intravenously E) Prescribe high- dose mucolytics and chest physiotherapy 3. A 5. 6- year- old male with type 2 diabetes mellitus has normal cardiac and renal function but has failed to achieve adequate control of his diabetes with diet and multiple oral agents. His BMI is 3. 0. 1 kg/m. A1c level is 9. 1%.

Find World TB Day resources, activities & more. Visit CDC’s latent TB infection online hub. See newly released TB Treatment Guidelines. See the Take on Latent. 132 qa interview questions and answers pdf 1. 132 QA interview questions and answers Useful materials: Complete Interview Questions and Answers Guide and Tips to frequently asked questions with answers. Most common mock interview questions and best answers. I need to draw text using gl methods only. After reading the red book i.

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Which one of the following is most likely to be beneficial in combination with insulin and diet therapy in this patient? A) Acarbose (Precose) B) Glimepiride (Amaryl) C) Metformin (Glucophage) D) Pioglitazone (Actos) E) Repaglinide (Prandin) 1 4. You see a 7. 8- year- old male in the hospital the day after his hip- replacement surgery. He has not voided in the past 1. A urethral catheter is placed and 5. L of urine is removed from his bladder. Which one of the following is most likely to improve the success rate of a voiding trial?

A) Using a specialized catheter coud. A 2. 2- year- old college student comes to your office to discuss her several- year history of abdominal pain and constipation. It has gotten worse since she returned to school this fall. She describes crampy pain and bloating that eases after defecation.

Her bowel movements are firm and difficult to pass, and occur about every 3 days on average. Her symptoms have not included vomiting, weight loss, blood in the stool, or melena. Her menses are regular and she is an otherwise healthy young woman. Her family history is negative for any gastrointestinal or genitourinary diseases. On examination you find her abdomen to be soft and without masses, with no tenderness to palpation.

Which one of the following would be most appropriate at this time? A) A therapeutic trial of increased soluble fiber intake B) A therapeutic trial of lubiprostone (Amitiza) C) Abdominal ultrasonography D) Abdominal CT E) Colonoscopy 6. Which one of the following is a proven strategy to reduce anterior cruciate ligament tears in high- school athletes? A) The use of neoprene knee sleeves by all athletes competing in high- risk sports B) Consistent inclusion of long- distance running in practice sessions C) Structured exercises stressing balance, muscle strength, and proprioception D) Prohibiting girls from playing on boys’ sports teams E) Increased enforcement of penalties involving dangerous plays 2 7. A 7. 0- year- old female presents with recurrent episodes of cough, voluminous sputum, and dyspnea.

She is a nonsmoker and has never smoked, except for a few cigarettes in her teens. Her past, family, and occupational histories do not suggest a cause for pulmonary or liver disease. Her examination is within normal limits except for the lung examination, which reveals crackles at both lung bases on auscultation. A chest radiograph shows nonspecific markings at both bases.

The most appropriate next step in her workup would be A) a PPD skin test B) high- resolution CT C) an ! D) referral for bronchoscopy 8. A previously healthy 2. On examination she has tenderness over the maxillary sinus on the left.

Which one of the following would be most appropriate for treatment of this patient’s condition? A) Intranasal saline flushes B) Intranasal antihistamines C) Oral antihistamines D) Oral antibiotics E) Reassurance only 9. A 5. 0- year- old female presents with a 3- week history of a moderately pruritic rash, characterized by flat- topped violaceous papules 3–4 mm in size. The lesions are located primarily on the volar wrists and forearms, lower legs, and dorsa of both feet. Ten days after the rash first appeared she went to the emergency department and was treated for “possible scabies,” but the treatment has made little or no difference.

Which one of the following treatments is indicated at this time? A) Clobetasol (Cormax, Temovate) 0. B) Permethrin 5% cream C) Tacrolimus (Protopic) 0. D) Triamcinolone 0. Which one of the following children should be referred immediately for evaluation of speech delay? A) A 1. 2- month- old who babbles but speaks no words B) An 1. C) A 2- year- old who has a vocabulary of 2.

D) A 2- year- old who is unable to follow three- step directions E) A 3- year- old who has a vocabulary of 5. A 2. 3- year- old female presents with recurrent unprovoked epistaxis. The patient’s mother is known to have hereditary hemorrhagic telangiectasia. Contrast echocardiography is recommended to screen for which one of the following frequently associated conditions? A) Atrioseptal defect B) Ventricular septal defect C) Aortic root aneurysm D) Pulmonary arteriovenous malformation E) Myocardial perfusion defects 1. A 6. 5- year- old male who has been in good health presents to your office with a 2- day history of a sensation of pressure and hearing loss in his left ear. A physical examination and a thorough neurologic examination are both unremarkable.

Both tympanic membranes are normal. An audiogram shows a 3. Placing a vibrating tuning fork in the midline of the forehead reveals sound lateralizing to the right ear.

Which one of the following would be most appropriate at this point? A) CT B) A CBC, metabolic profile, and thyroid studies C) Nifedipine (Procardia) D) Acyclovir (Zovirax) E) Oral corticosteroids 1. Which one of the following is true concerning the use of hemoglobin A1c levels to diagnose diabetes mellitus? A) A level > 6. B) Results can be misleading in patients with sickle cell disease C) The test is equally sensitive in African- Americans and whites D) The test is useful to diagnose diabetes during pregnancy 1.

A 5. 0- year- old female presents for evaluation of dyspnea that tends to occur with exercise. She has a 4. 0–pack- year history of smoking and has been diagnosed with exercise- induced asthma.

She denies any other medical problems. You perform spirometry and find that the expiratory loop is normal and that she has a flattened inspiratory loop. What is the most likely diagnosis? A) Vocal cord dysfunction B) COPD C) Asthma D) Restrictive lung disease 4 1. A previously healthy 2. She also complains of right flank pain, fevers and chills, and nausea without vomiting. She has a decreased appetite, but has been able to drink liquids.

On examination she has a temperature of 3. She has mild suprapubic tenderness and right costovertebral angle tenderness. A urinalysis shows microscopic pyuria, hematuria, and a positive leukocyte esterase test. Additional laboratory studies are notable for leukocytosis with a left shift, but are otherwise normal, including a negative pregnancy test. The patient does not have allergies to any antibiotics.

Which one of the following would be most appropriate for this patient? A) Outpatient management with oral amoxicillin B) Outpatient management with oral ciprofloxacin (Cipro) C) Outpatient management with oral nitrofurantoin (Macrodantin) D) Inpatient management with intravenous ceftriaxone (Rocephin) E) Inpatient management with intravenous levofloxacin (Levaquin) 1.

An 8. 2- year- old female is hospitalized for pneumonia and sepsis. She has advance directives in place. Should it become necessary, the patient’s decision- making capacity is determined by A) the spouse or next of kin B) the attending physician C) a consulting psychiatrist D) the hospital ethics committee E) a judge, at the request of hospital social services or the physician 1. A 6. 7- year- old female presents with the inability to smell. She is in good health, and her only medical problem is osteoporosis, treated with alendronate (Fosamax).

She says she has no sinus or nasal symptoms. A physical examination is normal including an ear, nose, and throat examination.

Which one of the following would be most appropriate at this point? A) Discontinuing the alendronate B) An anti- tissue transglutaminase antibody test C) A serum vitamin D level D) MRI of the brain 5 1. The American Heart Association recommends a goal blood pressure of ! Hg for patients with A) heart failure B) pulmonary hypertension C) atrial fibrillation D) angina pectoris E) chronic kidney disease 1. A 7. 8- year- old female has chronic symptomatic orthostatic hypotension, likely related to diabetic autonomic dysfunction, which has failed to respond to nonpharmacologic treatment. Her current medications include metformin (Glucophage), 1. Lipitor), 4. 0 mg daily; aspirin, 8.

Lantus), 2. 4 units at bedtime. Which one of the following would be the most effective therapy for her orthostatic hypotension? A) Clonidine (Catapres) B) Midodrine C) Pseudoephedrine D) Terbutaline E) Theophylline 2.

More Must- Know Data Science Interview Questions and Answers. The post 2. 1 Must- Know Data Science Interview Questions and Answers was the most viewed post of 2. For 2. 01. 7, KDnuggets Editors bring you 1. Data Science Interview Questions and Answers. Because some of the answers are quite lengthy, we will publish them in 3 parts over 3 weeks. This is part 1, which answers the 6 questions below.

Here is part 2 and part 3. This post answers questions: Q1. What are Data Science lessons from failure to predict 2. US Presidential election (and from Super Bowl LI comeback)Q2. What problems arise if the distribution of the new (unseen) test data is significantly different than the distribution of the training data? Q3. What are bias and variance, and what are their relation to modeling data?

Q4. Why might it be preferable to include fewer predictors over many? Q5. What error metric would you use to evaluate how good a binary classifier is?

What if the classes are imbalanced? What if there are more than 2 groups? Q6. What are some ways I can make my model more robust to outliers? Q1. What are Data Science lessons from failure to predict 2.

US Presidential election (and from Super Bowl LI comeback)Gregory Piatetsky answers: Just before the Nov 8, 2. Hillary Clinton an edge of ~3% in popular vote and 7.

Nate Silver's Five. Thirty. Eight had the highest chances of Trump Victory at ~3.

New York Times Upshot and Princeton Election Consortium estimated only ~1. Huffington Post gave Trump only 2% chance of victory. So what are the lessons for Data Scientists? To make a statistically valid prediction we need. Events can placed on the scale from deterministic (2+2 will always equal to 4) to strongly predictable (e. Pollsters need to get a representative sample, estimate the likelihood of a person actually voting, make many justified and unjustified assumptions, and avoid following their conscious and unconscious biases.

In the case of US Presidential election, correct prediction is even more difficult because of the antiquated Electoral college system when each state (except for Maine and Nebraska) awards the winner all its votes in the electoral college, and the need to poll and predict results for each state separately. The chart below shows that in 2. US presidential elections pollsters were off the mark in many states. They mostly underestimated the Trump vote, especially in 3 critical states of Michigan, Wisconsin, and Pennsylvania which all flipped to Trump. Source: @Nate. Silver.

Nov 9, 2. 01. 6. A few statisticians like Salil Mehta @salilstatistics were warning about unreliability of polls, and David Wasserman of 5. Sep 2. 01. 6 How Trump Could Win The White House While Losing The Popular Vote, but most pollsters were way off.

So a good lesson for Data Scientists is to question their assumptions and to be very skeptical when predicting a weakly predictable event, especially when based on human behavior. Other important lessons are. Examine data quality - in this election polls were not reaching all likely voters. Beware of your own biases: many pollsters were likely Clinton supporters and did not want to question the results that favored their candidate. For example, Huffington Post had forecast over 9.

Clinton Victory. See also other analyses of 2. Note: this answer is based on a previous KDnuggets post: http: //www. We had another example of statistically very unlikely event happen in Super Bowl LI on Feb 5, 2. ESPN estimated Falcons win probability at that time at almost 1. Salil Mehta tweet Salil Mehta tweet, Feb 6, 2. Never before has a team lost a Super Bowl after holding such advantage.

You need to understand the risk factors when dealing with such events, and try to avoid using probabilities, or if you have to use numbers, have a wide confidence range. Finally, if the odds seem to be against you but the event is only weakly predictable, go ahead and do your best - sometimes you will be able to beat the odds. Q2. What problems arise if the distribution of the new (unseen) test data is significantly different than the distribution of the training data? Gregory Piatetsky and Thuy Pham answer: The main problem is that the predictions will be wrong ! If the new test data is sufficiently different in key parameters of the prediction model from the training data, then predictive model is no longer valid. The main reasons this can happen are sample selection bias, population drift, or non- stationary environment.

Sample selection bias. Here the data is static, but the training examples have been obtained through a biased method, such as non- uniform selection or non- random split of data into train and test. If you have a large static dataset, then you should randomly split it into train/test data, and the distribution of test data should be similar to training data.

Covariate shift aka population drift. Here the data is not static, with one population used as a training data, and another population used for testing.(Figure from http: //iwann.

Invited. Talk- FHerrera- IWANN1. Sometimes the training data and test data are derived via different processes - eg a drug tested on one population is given to a new population that may have significant differences. As a result, a classifier based on training data will perform poorly. One proposed solution is to apply a statistical test to decide if the probabilities of target classes and key variables used by the classifier are significantly different, and if they are, to retrain the model using new data. Non- stationary environments. Training environment is different from the test one, whether it's due to a temporal or a spatial change.

This is similar to case b, but applies to situation when data is not static -  we have a stream of data and we periodically sample it to develop predictive models of future behavior. Another typical case is customer analytics where customer behavior changes over time. Neural Computation 1. What are bias and variance, and what are their relation to modeling data? Matthew Mayo answers: Bias is how far removed a model's predictions are from correctness, while variance is the degree to which these predictions vary between model iterations. Bias vs Variance, Image source.

As an example, using a simple flawed Presidential election survey as an example, errors in the survey are then explained through the twin lenses of bias and variance: selecting survey participants from a phonebook is a source of bias; a small sample size is a source of variance. Minimizing total model error relies on the balancing of bias and variance errors. Ideally, models are the result of a collection of unbiased data of low variance. Unfortunately, however, the more complex a model becomes, its tendency is toward less bias but greater variance; therefore an optimal model would need to consider a balance between these 2 properties. The statistical evaluation method of cross- validation is useful in both demonstrating the importance of this balance, as well as actually searching it out.

The number of data folds to use - - the value of k in k- fold cross- validation - - is an important decision; the lower the value, the higher the bias in the error estimates and the less variance. Bias and variance contributing to total error, Image source. Conversely, when k is set equal to the number of instances, the error estimate is then very low in bias but has the possibility of high variance.

The most important takeaways are that bias and variance are two sides of an important trade- off when building models, and that even the most routine of statistical evaluation methods are directly reliant upon such a trade- off. On next page, we answer. Why might it be preferable to include fewer predictors over many? What error metric would you use to evaluate how good a binary classifier is? What are some ways I can make my model more robust to outliers?