Null and alternative hypothesis (1 Viewer)

Hivaclibtibcharkwa

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Can someone help me with these question, like with question b would the null hypothesis be that it’s less than 70 or would the alternative hypothesis say that?62AC07E2-A2D9-4B99-A1B6-96309573DBD7.png
 
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cossine

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Can someone help me with these question, like with question b would the null hypothesis be that it’s less than 70 or would the alternative hypothesis say that?
The null hypothesis is always an equality. The reason for this is computation.

Because the definition p-value is

p-value = P(getting test statistic that is more contradictory or equally contradictory to the null hypothesis | H0 )

It may help to read Probability and Statistics for Engineering Sciences by Jay L. Devore

It will explain things in more detail
 

Hivaclibtibcharkwa

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The null hypothesis is always an equality. The reason for this is computation.

Because the definition p-value is

p-value = P(getting test statistic that is more contradictory or equally contradictory to the null hypothesis | H0 )

It may help to read Probability and Statistics for Engineering Sciences by Jay L. Devore

It will explain things in more detail
Ah sorry just realised I didn’t put in the imahe
 

jimmysmith560

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In general, we reject the null hypothesis if the p-value is less than the significance level α.

If the alternative hypothesis contains the not‐equal‐to symbol (≠), the hypothesis test is a two‐tailed test. Otherwise, all other tests are one-tailed.

If needed, below are solutions to each part, based on the above information. As cossine mentioned, definitely try to attempt the question(s) first to see if you can apply your understanding in your working:

Part (a):

Suppose is the average age of Sydney residents; then is , and is . Note that this is a one-tailed hypothesis test. Here, the p-value 0.0170 is less than the significance level . So we reject the null hypothesis.

Conclusion: this sample information does indicate that the mean age in Sydney has increased from 35 years.

Part (b):

Let be the average weight of this population; then is , and is . This is a one-tailed test. The standard deviation of weights in this population is . Here, the p-value 0.001 is less than the significance level . So we reject the null hypothesis.

Conclusion: the sample data do provide enough evidence for us to conclude that the mean weight for the population is less than 70 kg.

Part (c):

Let be the average IQ score of this population; then is , and is . This is a two-tailed test. Here, the p-value 0.095 is greater than the significance level . So we do not reject the null hypothesis.

Conclusion: on the basis of these data, we cannot conclude that the mean IQ score for this population is not 100.

I hope this helps! :D
 

Hivaclibtibcharkwa

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The null hypothesis is always an equality. The reason for this is computation.

Because the definition p-value is

p-value = P(getting test statistic that is more contradictory or equally contradictory to the null hypothesis | H0 )

It may help to read Probability and Statistics for Engineering Sciences by Jay L. Devore

It will explain things in more detail
Can it also be the greater than or equal to symbol?
3:37 of this video
 

cossine

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Can it also be the greater than or equal to symbol?
3:37 of this video
So if you have

H0: mean_weight >= 70
Ha: mean_weight <70

Reject the null hypothesis would be equivalent to rejecting H0: mean_weight=70

For computing the z-value you would have mean_weight=70.
 

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