The average weight loss of a patient following a new type of bariatric surgery is 18 kg. The standard deviation of weight loss is 3kg. Assuming the weight loss is normally distributed, what percentage of patients with loss between 9 and 27 kg?
Correct Answer E:
99.7% of values of a normally distributed variable lie within 3 standard deviations of the mean.
Normal distribution:
The normal distribution is also known as the Gaussian distribution or 'bell-shaped' distribution. It describes the spread of many biological and clinical measurements.
Properties of the Normal distribution:
Standard deviation:
A small study looks at the weight of patients diagnosed with type 2 diabetes mellitus. Overall 64 patients were reviewed. The average weight was 81 kg, with a standard deviation of 12 kg.
What is the standard error of the mean?
Standard error of the mean = standard deviation / square root (number of patients).
The standard error of the mean is calculated by the standard deviation / square root (number of patients) = 12 / square root (64) = 12 / 8 = 1.5
Standard error of the mean:
The standard error of the mean (SEM) is a measure of the spread expected for the mean of the observations - i.e. how 'accurate' the calculated sample mean is from the true population mean.
Key points:
A confidence interval for the mean can be calculated in a similar way to that for a single observation, i.e. The 95% confidence interval:
Which foramen does the oculomotor nerve go through?
Correct Answer A:
Foramina of the skull:
Questions asking about foramina of the skull have come up in the exam in previous years. Below is a brief summary of the major foramina, please see the Wikipedia link for a full list.
In terms of the cell cycle, which one of the following phases determine the length of the cell cycle:
Correct Answer C:
Cell cycle:
A study is performed to assess the correlation between age and systolic blood pressure.
Which one of the following statements regarding the calculation of the correlation coefficient, r, is incorrect?
Correct Answer D:
Linear regression is needed to predict systolic blood pressure in this scenario.
Correlation and linear regression:
Two measurements, or variables, may be plotted on a scatter plot. For example, age may be marked along the x axis and systolic blood pressure along the y axis.
Correlation:
The correlation coefficient (sometimes referred to as Pearson's product-moment coefficient) indicates how closely the points lie to a line drawn through the plotted data. It is denoted by the value r which may lie anywhere between -1 and 1.
For example:
Whilst correlation coefficients give information about how one variable may increase or decrease as another variable increases they do not give information about how much the variable will change. They also do not provide information on cause and effect.
Linear regression:
In contrast to the correlation coefficient, linear regression may be used to predict how much one variable changes when a second variable is changed. A regression equation may be formed, y = a + bx, where:
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