Answer:
0.505 g is <em>more than</em> the advertised amount by 0.005 g.
Step-by-step explanation:
0.5 = 0.500, so 0.505 is <em>more than</em> the advertised amount.
"Too little" or "too much" is a judgment based on some criteria not specified by the problem statement. Usually a supplier will want to ensure the customer receives full measure, so will adjust the capsule-making machine to provide at least the advertised amount. Whether it is "too little" or "too much" depends on your point of view and the dangers or costs of deviating from the advertised amount.
0.505 - 0.500 = 0.005 . . . . the difference between the actual and advertised amounts, in grams.
The number is x
it is negative
the square is 28 more than 3 times itself
x²=28+3x
minus (28+3x)
x²-3x-28=0
factor
(x-7)(x+4)=0
set to zero
x-7=0
x=7
this is not the answer because we were told the number was negative
x+4=0
x=-4
correct
the number is -4
test
(-4)²=28+3(-4)
16=28-12
16=16
check
the number is -4
Answer:
The graph is decreasing
Step-by-step explanation:
Starting at -1, the graph goes down to its value at 1
The graph is decreasing
Complete Question
Statistics professors believe the average number of headaches per semester for all students is more than 18. From a random sample of 15 students, the professors find the mean number of headaches is 19 and the standard deviation is 1.7. Assume the population distribution of number of headaches is normal.the correct conclusion at
is?
Answer:
There is no sufficient evidence to support the professor believe
Step-by-step explanation:
From the question we are told that
The population mean is 
The sample size is 
The sample mean is 
The standard deviation is 
The level of significance is 
The null hypothesis is 
The alternative hypothesis is 
The critical value of the level of significance from the normal distribution table is

The test hypothesis is mathematically represented as

substituting values


Looking at the value of t and
we can see that
so we fail to reject the null hypothesis.
This mean that there is no sufficient evidence to support the professor believe