by | Sep 13, 2022 | Statistics
1. What assumption must we test to include a variable as a blocking factor?
2. Recognize the IV, DV, block and create a table for the following research statement.
“A company is planning to investigate the motor skills or elderly population. The company separates the target population into three age categories: 60 – 69, 70 – 79, and above 80 then randomly assign the participants in the study to one of the three task conditions. After individuals have completed the task, their performance will be compared.”
3. Use the data “Lab 3” with the research question to perform a fine report.
*age “1”:60-69, “2”: 70-79 and “3”: above 80.
THE ANSWER KEY WAS PROVIDED IN THE WEEK 3 FILES – PLEASE PROVIDE AN INSIGHT (1-2 paragraphs) ON ANOVA BLOCKING or THIS EXAMPLE OR CLASS LEARNINGS TO DATE.
For example, explain the next steps to be taken in the Lab 3 example – expand to include the 50-59 groups or new motor skill tes.
by | Sep 13, 2022 | Statistics
On the document ‘Fese.docx’, please add for Research Question 3
a T_TEST and for Research Question 5 a SPEARMAN CORRELATION. Note, Independent Variable: Research question 5 relate to survey questions 30 and 31
NOTE
The following research questions and hypotheses will be explored during this study:
RQ1: What are African-born immigrants’ current knowledge on policies related to health insurance coverage, immigration status (visa type), and a usual source of care during the COVID-19 pandemic?
RQ2: Does the immigration status (visa type) of African-born immigrants significantly affect their access to a usual source of care (i.e., emergency room, PCP, community clinic) during the COVID-19 pandemic?
H02: Immigration status does have an effect on African-born immigrants’ access to a usual source of care (i.e., emergency room, PCP, community clinic) during the COVID-19 pandemic?
Ha2: Immigration status does have an effect on the access to a usual source of care (i.e., emergency room, PCP, community clinic) for African-born immigrants during the COVID-19 pandemic?
RQ3: Does access to transnational resources (i.e., social support from friends/family/community in host country, financial support friends/family/community in native country, and physician support in native country) significantly affect access to a usual source of care (i.e., emergency room, PCP, community clinic) by African-born immigrants during the COVID-19 pandemic?
H03: There is no significant statistical effect of transnational resources (i.e., social support from friends/family/community, financial support friends/family/community in native country, and physician support in native country) on access to a usual source of care (i.e., emergency room, PCP, community clinic) with reference to African-born immigrants during COVID-19.
Ha3: Access to transnational resources ( (i.e., social support from friends/family/community in host country, financial support friends/family/community in native country, and physician support in native country) does have an effect on the access to a usual source of care (i.e., emergency room, PCP, community clinic) by African-born immigrants during COVID-19.
RQ4: Does an African-born immigrant’s country of origin ( i.e., East Africa, West Africa, Central Africa, North Africa, and South Africa) significantly affect their knowledge of and satisfaction with the U.S. health care system during COVID-19?
H04: African-born immigrant’s country of origin ( i.e., East Africa, West Africa, Central Africa, North Africa, and South Africa) does not significantly affect their knowledge of and satisfaction with the U.S. healthcare system during COVID-19.
Ha4: African-born immigrant’s country of origin ( i.e., East Africa, West Africa, Central Africa, North Africa, and South Africa) does significantly affect their knowledge of and satisfaction with the U.S. health care system during COVID-19.
RQ5: Is there a statistically significant relationship between African-born immigrant’s cultural health beliefs ( i.e., the use of traditional medicine/healing practices and religious/ spirituality practices) and the number of visits annually to a usual source of care (i.e., emergency room, PCP, community clinic) during the COVID-19 pandemic?
H05: There is no statistically significant relationship between African-born immigrants’ cultural health beliefs ( i.e., use of traditional medicine/healing practices, religious and spirituality practices) and the number of visits annually to a usual source of care (i.e., emergency room, PCP, community clinic) during the COVID-19 pandemic?
Ha5: There is a statistically significant relationship between African-born immigrants’ cultural health beliefs ( i.e., use of traditional medicine/healing practices, religious and spirituality practices) and the number of visits annually to a usual source of care (i.e., emergency room, PCP, community clinic) during the COVID-19 pandemic?
by | Sep 13, 2022 | Statistics
To Prepare
Review the Learning Resources, including “Create a Table” instructions on how to create a table in Word.
Download and review the Howell Excel Data Set found in this week’s Learning Resources.
Download and review the Howell Data Set Sheet.
Using MS Word, complete the following:
Create a grouped frequency distribution table using the ADD-like behavior score (ADDSC).
The table should have two columns: the interval column and the frequency column. There should not be more than 10 intervals used. Place the table into the discussion board.
From the grouped frequency table, explain why you chose the intervals you did to divide the data.
Analyze how many frequencies you had for each of the intervals in your data.
Explain what your frequency table could tell us about the data collected for this variable.
by | Sep 13, 2022 | Statistics
Choose one variable from the Howell Excel Data Set that is a continuous variable, not a categorical variable. Use the first 10 scores for that variable and conduct the following summation notations. Please show all your work:
Calculate each value requested for first 10 scores of the continuous variable you choose:
ΣX2
Σ(X + 1)
Explain how this information might help you when looking at a collection of data for a variabl
by | Sep 8, 2022 | Statistics
Understanding hypothesis tests can be difficult. The important thing to keep in mind is that the purpose of a hypothesis test is to say something about an entire population based on only a sample from the population. There is always the possibility that you can reach a wrong conclusion. Actually, there are two ways you can be wrong with a hypothesis test.
The first way is to reject a true null hypothesis. In this case, that means rejecting a null hypothesis that is really true. In other words–you shut down and recalibrate a machine that is really working correctly. This is called a Type I error.
The second way you can go wrong is to fail to reject a false null hypothesis. In this case, the machine needs to be calculated but your test concludes everything is okay. So you would keep producing bags of seed that are less than advertised, maybe leading to lawsuits or a bad reputation for your brand. This is called a Type II error.
How do we control the probability of a type I error in a hypothesis test?
by | Sep 7, 2022 | Statistics
Get the DataFile of CEOTime (attached).
Calculate the number of classes by using class width of two hours.
Set the lower class limit of the first class to include the lowest amount of time spent I the data set.
Tally the frequency in each class.
Get relative frequency, percent frequency, and cumulative frequency
Comment on the shape of the distribution. Interpret the pattern of how CEOs spend their day in meetings.
Upload the final frequency distribution table.
