Answer:
Statistical error is the difference between the estimated or approximated value and the true value.
<u>Two Possible Types of Statistical Error</u>
Type I Errors occur when we reject a null hypothesis that is actually true; the probability of this occurring is denoted by alpha (a).
Type II Errors are when we accept a null hypothesis that is actually false; its probability is called beta (b).
<u>Example </u>
You test whether a new drug intervention can alleviate symptoms of an autoimmune disease.
A Type I error happens when you get false positive results: you conclude that the drug intervention improved symptoms when it actually didn’t. These improvements could have arisen from other random factors or measurement errors.
A Type II error happens when you get false negative results: you conclude that the drug intervention didn’t improve symptoms when it actually did. Your study may have missed key indicators of improvements or attributed any improvements to other factors instead.
Answer:
34 is the number
Step-by-step explanation:
105/7=15+19=34
34-19=15
15•-7=-105
Answer:
10 km
Step-by-step explanation:
Running distance = 8 km
Sprinting distance = 0.5
Climbing distance = <u> 1.5 </u>
TOTAL = 10 km
Jamal travelled 10 km in total.
11 * 6.5 = 71.5
<span>15 - 71.5 = -56.5</span>
Answer:
46.58%
Step-by-step explanation:sorry if wrong
