Question 1

Which of the following statements usually determines the acceptable range when evaluating quality control results?
A) The range that includes 75% of the results
B) The range encompassed by ±2.5 standard deviations
C) The 95% confidence interval of the mean
D) The central 68% of results

Accepted Answer

The 95% confidence interval of the mean is commonly used to determine the acceptable range in quality control evaluations because it statistically represents where 95% of the data points are expected to fall, assuming a normal distribution. This provides a standard for assessing whether a particular result falls within an acceptable range or indicates a potential issue that needs to be addressed.

Question 2

Which of the following is an example of nominal type data?
A) Numbers applied to numeric variables for example, cholesterol result of 250 mg/dL
B) Numbers applied to nonnumeric variables for example blood types could be coded as group O=1, group A= 2 etc.
C) Numbers that are discrete and ordered for example, 4 = most severe injury, 2 = a moderately severe and 1 = a minor injury
D) Arithmetic mean

Accepted Answer

Nominal data refers to data that is used to label variables without a quantitative value, essentially categorizing variables. In choice B, blood types are categorized into groups and assigned numbers, which is a classic example of using numbers to represent categories, hence nominal data.

Question 3

A 1_3s quality control rule violation is defined as: A) One control result that exceeds ±3 s. B) One control result that exceeds ±1.3s. C) Three consecutive controls results that exceed ±3 s. D) One control result that exceeds ±4 s.

Accepted Answer

The 1_3s rule is defined as one control result exceeding ±3 standard deviations (s) from the mean.

Question 4

Which statement listed below is a reason to reject an analytical run?
A) One control result exceeds above +1 standard deviation and the second control result exceeds -1 standard deviation from the mean.
B) Two consecutive control results exceed 2 standard deviations above or below the mean.
C) Four control results steadily increase in value but are less than ±1 standard deviation from the mean.
D) Three consecutive control results exceed plus or minus 1 standard deviation from the mean.

Accepted Answer

Two consecutive control results exceeding 2 standard deviations above or below the mean indicate a lack of control and potential systematic error, warranting rejection of the analytical run according to Westgard rules.

Question 5

Which of the following is an example of an inferential statistic?
A) Mean
B) Standard deviation
C) F- test
D) Correlation coefficient

Accepted Answer

The F-test is an example of an inferential statistic because it is used to determine if there are significant differences between groups, which involves making inferences about populations based on sample data.

Question 6

A graph that shows the difference between your laboratory result and a comparative method results along the x-axis and the percent difference along the y-axis is referred to as which of the following?
A) Levy-Jennings graph
B) Linear regression graph
C) CUSUM graph
D) Bias graph

Accepted Answer

A bias graph is used to plot the difference between a laboratory's test results and a comparative method's results against the percent difference. This type of graph helps in identifying any systematic error (bias) in the laboratory's results compared to the standard or comparative method.

Question 7

Which of the following practices is inappropriate when establishing quality controls ranges?
A) Exclusion of any quality control results greater than ±2 standard deviation from the mean
B) Compare your data to the manufacturer of the quality control material.
C) Gather quality control data for a long period of time if necessary.
D) Using control results from all shifts on which the assay is performed

Accepted Answer

Excluding any quality control results greater than ±2 standard deviation from the mean is inappropriate because it can lead to a biased estimation of the mean and standard deviation, potentially masking issues with assay performance. Quality control ranges should be established based on a representative sample of data, including outliers, to accurately reflect the performance of the assay.

Question 8

Which of the following statistics is used to qualify the strength of the relationship between two variables?
A) z- value
B) standard error of the difference
C) Confidence interval
D) Correlation coefficient

Accepted Answer

The correlation coefficient is specifically used to quantify the degree to which two variables are related. It measures the strength and direction of a linear relationship between two variables.

Question 9

An important difference between parametric statistics and nonparametric statistics is that nonparametric statistics is distribution free, whereas parametric statistics:
A) Assumes linearity.
B) Is sensitive to gender and age.
C) Presumes a Gaussian distribution.
D) Accepts all outliers.

Accepted Answer

Parametric statistics assume that the data follows a specific distribution, typically a Gaussian (normal) distribution. This assumption allows for the use of specific statistical tests that rely on this distributional assumption. Nonparametric statistics, on the other hand, do not require the data to follow any specific distribution, making them more flexible in handling data that does not fit the normal distribution.

Question 10

Recovery experiments, testing proficiency samples and estimating bias are all examples of procedures used to assess:
A) Accuracy.
B) Precision.
C) Coefficient of determination.
D) Total error.

Accepted Answer

Recovery experiments, testing proficiency samples, and estimating bias are all methods used to assess the accuracy of a measurement system. Accuracy refers to how close a measured value is to the true value, and these procedures help in evaluating this aspect by identifying and quantifying any deviations from the true value.

Question 11

A type II error is defined as which of the following?
A) A serious misinterpretation of quality control rule violation
B) Erroneously accepting the null hypothesis, with the result that a real difference is not detected.
C) Erroneously rejecting the null hypothesis or proclaiming a difference to exist when one does not
D) Ignoring a large bias between two methods

Accepted Answer

A type II error occurs when the null hypothesis is incorrectly accepted, meaning a real difference or effect exists but is not detected by the test.

Question 12

A significant limitation of least squares regression analysis is:
A) A large confidence intervals may result is false positives.
B) Outliers will not impact the results.
C) It may result in an incorrect decision of analytical reproducibility.
D) Nonlinearity of the data will affect both the slope and intercept.

Accepted Answer

Least squares regression assumes a linear relationship between the independent and dependent variables. If the data is nonlinear, this assumption is violated, affecting the accuracy of the slope and intercept estimates.

Question 13

Analysis of variance (ANOVA) is an appropriate statistics to evaluate three or more sets of data among each other, but it does NOT reveal:
A) Which set of data is bias.
B) Which set of data is most accurate.
C) Which set of data is most precise.
D) Which set of data is not in agreement with the other data.

Accepted Answer

The answer of Analysis of variance (ANOVA) is an appropriate...

Question 14

Deming's linear regression analysis attempts to:
A) Compensate for shortcomings of Passing and Bablok regression analysis.
B) Overcome shortfalls in the least squared method.
C) Overcome shortfall due to quality control failures.
D) Overcome issues related to the interpretation of a Student-t test.

Accepted Answer

Deming's linear regression analysis is designed to address limitations in the least squares method, particularly when both variables have associated error, providing a more accurate line of best fit in such scenarios.

Question 15

The McNemar statistics using a two by two contingency table is useful for evaluating which of the following?
A) Correlation between two qualitative assays for example urine ?-hCG
B) The degree of association between two sets of data
C) Correlation between two quantitative assays for serum ?-hCG
D) Determining the source of error in a qualitative assay

Accepted Answer

The McNemar test is specifically designed for evaluating the difference in proportions of paired nominal data, making it suitable for comparing two qualitative assays, such as urine ?-hCG tests, to see if there is a significant change in outcomes between the two tests on the same subjects.

Question 16

Linearity is useful for assessing:
A) Slope and bias of an analytical method.
B) A large correlation coefficient.
C) Intercept and p value of analytical method.
D) Slope and intercept of an analytical method.

Accepted Answer

Linearity is used to assess the slope and intercept of an analytical method, which indicates how well the method can produce results that are directly proportional to the concentration of analyte in the sample.

Question 17

The term patient demographics refers to which type of information that is entered into a laboratory information system?
A) Patient-specific information, for example, name, age, and date of birth
B) Patient-specific information, for example, the total volume of urine collected in a 24-hour period for a creatinine clearance
C) Patient-specific information, for example, their mother's and father's first and last name
D) Patient-specific information, for example, where they were born and their religious preference

Accepted Answer

Patient demographics typically include basic personal information such as name, age, and date of birth, which are essential for identifying and managing a patient's records in a laboratory information system.

Question 18

A cross-reacting compound in a serum sample may result in which of the following?
A) A reliable result
B) A precise result
C) An accurate result
D) A discordant result

Accepted Answer

A cross-reacting compound in a serum sample may interfere with the assay, leading to a discordant or inaccurate result, as it may bind to the assay's antibodies or detection system intended for the target analyte, thus producing misleading data.

Question 19

Proportional error in a method is characterized by which of the following?
A) The magnitude of the error stays the same over a wide concentration range.
B) The magnitude of the error increases as the concentration of analyte increases.
C) The magnitude of the error decreases as the concentration of analyte increases.
D) The magnitude of the error is inversely proportional to concentration.

Accepted Answer

Proportional error in a method means that the magnitude of the error increases in proportion to the increase in the concentration of the analyte. This type of error is directly related to the amount of substance being measured.

Question 20

A glucose result that is greater than the lower limit of detection of the method should be reported as which of the following?
A) Zero
B) Less than the detection limit value
C) The actual concentration value given by the analyzer or as calculated by the operator
D) Greater than the detection limit value

Accepted Answer

The answer of A glucose result that is greater than...

Quiz 3: Laboratory Statistics, Method Development and QC

Which of the following statements usually determines the acceptable range when evaluating quality control results?

Which of the following is an example of nominal type data?

A 13s quality control rule violation is defined as:

Which statement listed below is a reason to reject an analytical run?

Which of the following is an example of an inferential statistic?

A graph that shows the difference between your laboratory result and a comparative method results along the x-axis and the percent difference along the y-axis is referred to as which of the following?

Which of the following practices is inappropriate when establishing quality controls ranges?

Which of the following statistics is used to qualify the strength of the relationship between two variables?

An important difference between parametric statistics and nonparametric statistics is that nonparametric statistics is distribution free, whereas parametric statistics:

Recovery experiments, testing proficiency samples and estimating bias are all examples of procedures used to assess:

A type II error is defined as which of the following?

A significant limitation of least squares regression analysis is:

Analysis of variance (ANOVA) is an appropriate statistics to evaluate three or more sets of data among each other, but it does NOT reveal:

Deming's linear regression analysis attempts to:

The McNemar statistics using a two by two contingency table is useful for evaluating which of the following?

Linearity is useful for assessing:

The term patient demographics refers to which type of information that is entered into a laboratory information system?

A cross-reacting compound in a serum sample may result in which of the following?

Proportional error in a method is characterized by which of the following?

A glucose result that is greater than the lower limit of detection of the method should be reported as which of the following?

A 1_3s quality control rule violation is defined as: