I Need Assistance With My Homework Thank You Very Much

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Please help. I need assistance with my homework. Thank you very much.

“Ancient Greece and Athletics” Please respond to the following, using sources under the Explore heading as the basis of your response:

  • Describe the ancient Greek competitive character.
  • Compare the ancient Olympics (as a festival featuring athletics) to the Olympics today, identifying any major differences.
  • Explain what the Olympic rules regarding females and evidence, such as the “running girl” artifact, reveal about female status and Greek athletics in particular Greek city-states.

Explore

Ancient Greek Athletics and Female Status

  • Chapter 4 (p. 118), Olympics. Chapters 4 (pp. 113-114), women in Sparta; For Athens later, see pp. 137-8.
  • British Museum’s Running Girl artifact at http://culturalinstitute.britishmuseum.org/asset-viewer/bronze-figure-of-a-running-girl/5AFwcCa2vpvNdA?hl=en (click on ‘detail”); and https://chnm.gmu.edu/cyh/primary-sources/383.
  • Philadelphia’s Penn Museum on Women and Greek athletics at http://www.penn.museum/sites/olympics/olympicsexism.shtml
 
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I Need Assistance With The Attached Homework Which Entails 3 Medical Case Studie

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I need assistance with the attached homework, which entails 3 medical case studies.

 
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I Need Assistance With The Attached Nursing Related Short Answer

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I need assistance with the attached Nursing related short answer.

 
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I Need Assistance With The Following Discussion Question

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I need assistance with the following discussion question. I have attached the document that describes problems at the Columbus air processing center of the United Postal Service. After reading the attached ,please answer the following questions.  At least one reference is required.

The goal is to deliver letters and packages on time. It was found that 8.7% of the letters processed did not meet on-time delivery commitments. A Six Sigma project was started to address this issue. One outcome was the creation and documentation of a standardized process.

How might the Postal Service use systems to improve their process control? What is the current stage of operational effectiveness at the Columbus facility? Should the Postal Service consider ISO 9000 certification? Why or why not? They use p-charts to monitor performance; is this an appropriate statistical technique? What other statistical techniques would you recommend?

 
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I Need Assistance With The Script Theres Are Several Steps Part I Descriptive St

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I need assistance with the script. Theres are several steps.

1. Part I: Descriptive Statistics (Scenario A)

Scenario A: National Weather Service

Imagine you are a data analyst working at the National Weather Service. Your primary job is to analyze historical weather data for regions within the United States collected by the agency. Your analysis will lead to updating important weather pattern models based on historical trends and your findings will be published in academic journals. As you can see, it is critical for an analyst to provide accurate analysis of the data so that proper interpretations and publications can be achieved. You are now given a task to analyze historical weather data for the city of Manchester in New Hampshire. You will be using monthly weather data collected for the city of Manchester to help task.

Use the following table as a reference guide for the variables of interest for this project.

VariableDefinitionEMXPExtreme Maximum Precipitation (Highest monthly maximum precipitation) reported in tenths of a millimeter.EMXTExtreme Maximum Temperature (Highest monthly maximum temperature) reported in tenths of a degree Celsius.EMNTExtreme Minimum Temperature (Lowest monthly minimum temperature) reported in tenths of a degree Celsius.MMXTMean Maximum Temperature (Average monthly maximum temperature) reported in tenths of a degree Celsius.MMNTMean Minimum Temperature (Average monthly maximum temperature) reported in tenths of a degree Celsius.MNTMMean Temperature (Average monthly temperature) reported in tenths of a degree Celsius.

Step 1: Import your data set

You will be working with the Manchester Weather data set. To ensure that you analyze the correct data set, make the following edits to the function underneath “Step 1: Import your data set” in the Tool Panel on the left side of the screen.

Uncomment line 11 ???DATASET_NAME??? manchesterweather

Step 2: Calculate descriptive statistics for Extreme Maximum Temperature (EMXT)

You will need to calculate the following descriptive statistics for the variable EMXT:

Mean

Median

Variance

Standard Deviation

Minimum

Maximum

25th Percentile

75th Percentile

In order to perform these functions, you need to make the appropriate modifications to correct Python functions within the provided script. In other words, you should:

Uncomment lines 17 – 52 ???DATASET_NAME??? manchesterweather the

…for each of the required Python functions listed above.

Step 3: Calculate descriptive statistics for Extreme Maximum Precipitation (EMXP)

You will need to calculate the following descriptive statistics for the variable EMXP:

Mean

Median

Variance

Standard Deviation

Minimum

Maximum

25th Percentile

75th Percentile

In order to perform these functions, you need to make the appropriate modifications to associated Python functions listed within the provided script. In other words, you should:

Uncomment lines 56 – 89 ???DATASET_NAME??? manchesterweather the

for each of the required Python functions listed above.

2. Part I: Confidence Intervals (Scenario A)

Step 4: Construct confidence interval for population proportion

Construct a 99% confidence interval for the proportion of months with highest monthly maximum temperatures above 19 degrees celsius (EMXT>190). In order to perform this function, you need to make the appropriate modifications to the provided script. In other words, you should:

– – Uncomment – ???DATASET_NAME??? manchesterweather the ???Xvalue??? the appropriate

Step 5: Construct confidence interval for population mean

Construct a 95% confidence interval for average highest monthly maximum precipitation (EMXP). In order to perform this function, you need to make the appropriate modifications to the provided script. In other words, you should:

Uncomment lines 106 – 113 ???DATASET_NAME??? manchesterweather the

Step 6: Perform hypothesis test for population proportion

It is claimed that 67% of the months have highest monthly maximum temperatures above 19 degrees celsius (EMXT>190). Is there sufficient evidence to suggest that the proportion is 67%? Test this claim using a hypothesis test at 5% level of significance. In order to perform this function, you need to make the appropriate modifications to the provided script. In other words, you should:

– – Uncomment – ???DATASET_NAME??? manchesterweather the ???Xvalue??? the appropriate ???NULL_VALUE??? the appropriate the hypothesis the appropriate alternative hypothesis

Step 7: Perform hypothesis test for population mean

It is claimed that average highest monthly maximum precipitation is 28 millimeters (EMXP=280). Test this claim using a hypothesis test at 1% level of significance. In order to perform this function, you need to make the appropriate modifications to the provided script. In other words, you should:

Uncomment lines 131 – 139 ???DATASET_NAME??? manchesterweather the ???NULL_VALUE??? the appropriate the hypothesis the appropriate alternative hypothesis

step 8: Get your results

Once you have confirmed that your code is correct by passing each of the self-assessments, it is time to get the results of your statistical tests. First, you must uncomment all of the lines of your scripting file that are not instructional, as indicated below:

lines – Uncomment lines – Uncomment lines – Uncomment lines – Uncomment lines – Uncomment lines –

________________________________________________________________________________________________

Script::

####### Milestone 1 Python Script

import pandas as pd

import scipy.stats as st

from snhu_MAT243 import prop_1samp_ztest

from snhu_MAT243 import means_1samp_ttest

##Step 1: Import your data set

##—————————————————————————–

???DATASET_NAME??? = pd.read_csv(‘???FILENAME???’)

##Step 2: Calculate descriptive statistics

##—————————————————————————–

# print (‘Descriptive Statistics – Step 2’)

# print (”)

# print (‘Mean’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].mean())

# print (”)

# print (‘Median’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].median())

# print (”)

# print (‘Mode’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].mode())

# print (”)

# print (‘Minimum’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].min())

# print (”)

# print (‘Maximum’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].max())

# print (”)

# print (‘Mean’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].var())

# print (”)

# print (‘Standard Deviation’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].std())

# print (”)

# print (‘Describe’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].describe())

# print (”)

# print (”)

##Step 3: Calculate descriptive statistics

##—————————————————————————–

# print (‘Descriptive Statistics – Step 3’)

# print (”)

# print (‘Mean’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].mean())

# print (”)

# print (‘Median’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].median())

# print (”)

# print (‘Mode’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].mode())

# print (”)

# print (‘Minimum’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].min())

# print (”)

# print (‘Maximum’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].max())

# print (”)

# print (‘Mean’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].var())

# print (”)

# print (‘Standard Deviation’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].std())

# print (”)

# print (‘Describe’)

# print (???DATASET_NAME???[[‘???VARIABLE_NAME???’]].describe())

# print (”)

##Step 4: Construct confidence interval for population proportion

##—————————————————————————–

# print (‘Confidence Interval – Step 4’)

# n = ???DATASET_NAME???[[‘???VARIABLE_NAME???’]].count()

# x = (???DATASET_NAME???[[‘???VARIABLE_NAME???’]] > ???Xvalue???).values.sum()

# p = x/n*1.0

# stderror = (p * (1 – p)/n)**0.5

# print (st.norm.interval(0.99, p, stderror))

# print (”)

##Step 5: Construct confidence interval for population mean

##—————————————————————————–

# print (‘Confidence Interval – Step 5’)

# n = ???DATASET_NAME???[[‘???VARIABLE_NAME???’]].count()

# df = n – 1

# mean = ???DATASET_NAME???[[‘???VARIABLE_NAME???’]].mean()

# stdev = ???DATASET_NAME???[[‘???VARIABLE_NAME???’]].std()

# stderror = stdev/(n**0.5)

# print (st.t.interval(0.95, df, mean, stderror))

# print (”)

##Step 6: Perform hypothesis test for population proportion

##—————————————————————————–

# print (‘Hypothesis Test – Step 6’)

# n = ???DATASET_NAME???[[‘???VARIABLE_NAME???’]].count()

# x = (???DATASET_NAME???[[‘???VARIABLE_NAME???’]] > ???Xvalue???).values.sum()

# null_value = ???NULL_VALUE???

# alternative = ‘???TEST_TYPE???’

# print (prop_1samp_ztest(x, n, null_value, alternative))

# print (”)

##Step 7: Perform hypothesis test for population mean

##—————————————————————————–

# print (‘Hypothesis Test – Step 7’)

# n = ???DATASET_NAME???[[‘???VARIABLE_NAME???’]].count()

# df = n – 1

# mean = ???DATASET_NAME???[[‘???VARIABLE_NAME???’]].mean()

# std_dev = ???DATASET_NAME???[[‘???VARIABLE_NAME???’]].std()

# null_value = ???NULL_VALUE???

# alternative = ‘???TEST_TYPE???’

# print (means_1samp_ttest(mean, std_dev, n, null_value, alternative))

# print (”)

 
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I Need Assistance With This Assignment Can I Please Get Some Help With This

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I need assistance with this assignment. Can I please get some help with this? It is for a criminal behavior class.

To increase your knowledge of the field, choose three (3) publicized criminal acts. Describe and discuss how each of the three key sociological perspectives in the Schmalleger text explains the commission of the respective criminal act. Each criminal act must have been disposed of (by conviction or acquittal of the accused) within the last three (3) years, so be sure to include names, dates, places, descriptions, and sources for each act chosen. Feel free to include outside reference material as well, but only as supporting or critiquing your original analysis.

This assignment must be a neat, professional presentation on this subject. Proper punctuation, spelling, and usage of grammar are imperative.

 
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I Need Assistance With This Projectthank You

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I need assistance with this project

Thank you

 
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I Need Assistance With This Question I Do Not Know Which Formula To Use What Is

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I need assistance with this question. I do not know which formula to use.

What is the accumulated sum of the following stream of payments? $2,557 every year at the end of the year for 11 years at 8.00 percent, compounded annually. Please assist.

 
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I Need Assistance With Writing A Memo I Am The Vp Of Human Resources Writing A M

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I need assistance with writing a memo. I am the VP of Human Resources writing a memo to leadership in regards to my decision. Here is the case study:

The Problem: The Case of the Troubling Inquiry

At lunch one day a friend, who is an excellent mid-level scientist in the company in which you work, tells you she wants to talk with you about a problem. She has a suspicion that she is being paid less that her male colleagues and wants your help. You have just been doing some research and know that the women scientists are in fact being paid less than the men with comparable experience and comparable education in the field. The hiring practice had been to bring people in at the lowest possible salary. You know that the research shows that because women tend to be more tentative about salary, they don’t ask for top dollar. You have just completed a salary survey in your company and know that women scientists are currently being paid 10% less then men with the same credentials in many cases. Your preliminary work indicates that to bring the women into parity with the men will cost approximately $37,500 per quarter.

My decision: Do not give up any information about your research. Go to your CEO with your research and state that someone is inquiring about the issue. Make a recommendation for increasing salaries to avoid a lawsuit.

Business Communication CenterRobert F. Price College of Business30197Asp Avenue, Room 01Norman, Ok 567078. MEMO To: CEO, Steve JobFrom: VP of HR, Carole CecileDate: 7/25/2017Subject:…

 
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I Need Assistance With

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In [3] : import sqlite3 as dbimport pandas as pdfrom datetime import datetimefrom collections import defaultdictdisk_engine = db. connect ( ‘ file: prob0 . db?mode=ro’, uri=True)def load_data( ) :df = pd. read_sql_query ( “SELECT * FROM soccer_results”, disk_engine)return dfIn [4]: # Test: Exercise 0 (exposed)df = load_data ( )assert df . shape [ 0] == 22851, “Row counts do not match. Try loading the data again”assert df . shape[1] == 9, “You don’t have all the columns. Try loading the data again”print ( “n (Passed! ) “)df . head ( )(Passed! )Out [ 4 ] :date home_team away_team home_score away_score tournamentcitycountry neutral0 1994-01-02BarbadosGrenada0Friendly Bridgetown Barbados FALSE1994-01-02GhanaEgypt- NFriendlyAccraa FALSE2 1994-01-05Mali Burkina FasoFriendlyBamakoMali FALSE3 1994-01-09MauritaniaMali3Friendly Nouakchott Mauritania FALSE1994-01-11ThailandNigeriaFriendlyBangkokThailand FALSEEach row of this dataframe is a game, which is played between a “home team” (column home_team) and an “away team” (away_team). The number of goalsscored by each team appears in the home_score and away_score columns, respectively.Exercise 1 (1 point): Write an SQL query find the ten (10) teams that have the highest average away-scores since the year 2000. Your query should satisfy thefollowing criteria. It should return two columns:. team: The name of the teamave_goals: The team’s average number of goals in “away” games. An “away game” is one in which the team’s name appars in away_team and thegame takes place at a “non-neutral site” (neutral value equals FALSE).It should only include teams that have played at least 30 away matches. It should round the average goals value (ave_goals) to three decimal places.It should only return the top 10 teams in descending order by average away-goals.. It should only consider games played since 2000 (including the year 2000).Store your query string as the variable, query_top10_away, below. The test cell will run this query string against the input dataframe, df, defined above andreturn the result in a dataframe named offensive_teams. (See the test cell.)Note. The following exercises have hidden test cases and you’ll be awarded full points for passing both the exposed and hidden test cases.In [5]: query_top10_away =SELECT away_team, ROUND ( avg (away_score) , 3)FROM dataWHERE neutral is false and strftime( ‘ $H’, date) ; >= 2000GROUP BY away_team HAVING count ( *) >= 30ORDER BY ROUND ( avg ( away_score) , 3)DESC LIMIT 10;

 
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