Sinus rhythm is normal.
The left axis deviation means that the electrical activity goes to the left side more than normal. This can be a normal variant, due to high blood pressure or due to other problems.
OK, this means quite a lot. The poor R wave progression indicates a defect e.g. death of the heart muscle (myocardial infarction) but its non specific. You would expect to see the R wave increase in amplitude across the Chest leads V1-V4, so poor progression means a less than expected increase.
Left axis deviation indicates a swing in the electrical axis in the heart. The most common cause is a left anterior hemiblock (partial block in the front left of the heart) but other causes can be MI as described above. This is confirmed by the left bundle branch block, indicated a problem in electrical conduction from the middle lower part of your heart, spreading out like a U from the bottom.
Old anterior infarct, the cardiologist reckons that you may have had an old heart attack that affected the front wall of the heart, causing scars to form.
Yes. Consider the definition of the standard deviation. It is the square root of the variance from the mean. As a result, it can be said that the standard deviation is dependent on the mean.
It is a thing which is although "abnormal", but people still consider it as "good" to have. Like a "warm beer".
A large standard deviation means that the data were spread out. It is relative whether or not you consider a standard deviation to be "large" or not, but a larger standard deviation always means that the data is more spread out than a smaller one. For example, if the mean was 60, and the standard deviation was 1, then this is a small standard deviation. The data is not spread out and a score of 74 or 43 would be highly unlikely, almost impossible. However, if the mean was 60 and the standard deviation was 20, then this would be a large standard deviation. The data is spread out more and a score of 74 or 43 wouldn't be odd or unusual at all.
ask the people who made the show. I wouldn't consider the show a success.... Shadow is a strange guy, borderline emo....
You get iron levels and consider anemia of chronic disease.
Consider thatxd= x- Arithmetic meand211-1.5 = -0.50.2522-1.5 = 0.50.25=0.5Arithmetic mean = (1+2)/2 =1.5Standard deviation=ie .5= 0.70now Considerxd= x- Arithmetic meand211-2=-1122-2=0033-2=11Arithmetic mean= (1+2+3)/3 = 2 =2Standard deviation= = (2/2) = 1So the Standard deviation can increasenow Considerxd= x- Arithmetic meand211-1.25=-0.250.062522-1.25=0.750.562511-1.25=-0.250.062511-1.25=-0.250.0625Arithmetic mean= (1+2+1+1)/4= 1.25 = .75Standard deviation= = (0.75/4) = 0.4330So the Standard deviation can decreaseStandard deviation can either decrese or increase or remains the same
Standard deviation is a measure of the scatter or dispersion of the data. Two sets of data can have the same mean, but different standard deviations. The dataset with the higher standard deviation will generally have values that are more scattered. We generally look at the standard deviation in relation to the mean. If the standard deviation is much smaller than the mean, we may consider that the data has low dipersion. If the standard deviation is much higher than the mean, it may indicate the dataset has high dispersion A second cause is an outlier, a value that is very different from the data. Sometimes it is a mistake. I will give you an example. Suppose I am measuring people's height, and I record all data in meters, except on height which I record in millimeters- 1000 times higher. This may cause an erroneous mean and standard deviation to be calculated.
Each individual is different. If you don't have cramps at the age of twenty consider yourself lucky, but not abnormal.
Standard deviation is a measure of the dispersion of the data. When the standard deviation is greater than the mean, a coefficient of variation is greater than one. See: http://en.wikipedia.org/wiki/Coefficient_of_variation If you assume the data is normally distributed, then the lower limit of the interval of the mean +/- one standard deviation (68% confidence interval) will be a negative value. If it is not realistic to have negative values, then the assumption of a normal distribution may be in error and you should consider other distributions. Common distributions with no negative values are gamma, log normal and exponential.
Yes. Consider 1,1,1,1,1,3,5,5,5,5,5 and 0,3,3,3,3,3,3,3,3,3,5 Set 1: Range = 4, sd = 2.00 Set 2: Range = 5, sd = 1.14
An abnormal result of an ultrasound of the scrotum may reveal an absent or undescended testicle, an inflammation problem, testicular torsion, a fluid collection, abnormal blood vessels, or a mass.
Mean μ = 63.3 Standard deviation σ = 3.82 Standard error σ / √ n = 3.82 / √ 19 = 0.8763681 z = (xbar - μ) / (σ / √ n ) z = (61.6-63.3) / 0.876368 z = -1.9398