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Director of leadership and learning for has been conducting engagement surveys among its employees every two years to gain a deeper understanding of employees’ views on areas such as customer service

Scenario

The organization that you are a director of leadership and learning for has been conducting engagement surveys among its employees every two years to gain a deeper understanding of employees’ views on areas such as customer service, the organization’s overall strategy, job satisfaction, rewards and recognition, and training and development. The most recent survey was conducted this year, and the organization wants to carry out another survey in two years.

Prompt

Your task is to continue using your GROW model template you began in Module Two to complete the final three sections:

  • Identified Gaps—Obstacles
  • Goal Revision
  • A Way Forward—Action

Specifically, you must address the following rubric criteria:

  1. In the Identified Gaps—Obstacles section, describe obstacles that might prevent the focus areas you previously identified moving from current state to future state. Consider the following in your response:
    1. Skill gaps, organizational culture, and resources among other things
  2. In the Goal Revision section, for each of the goals you created previously, describe whether they need to be revised:
    1. For the goals that do need to be revised, provide a revision and explain your changes based on obstacles you identified above.
    2. For the goals that do not need to be revised, provide rationale for why this goal should remain the same. Support your response.
  3. In the A Way Forward—Action section, recommend an actionable step that should be taken in order to close the gap between current state and desired future state for each identified focus area and related goal. Your response should include the following for each actionable step:
    1. An explanation on what the step will entail
    2. Identification of stakeholders who will need to be involved
    3. Justification for how this step will help close the gap between current state and desired future state

What to Submit

Submit your answers in the GROW Model Template that you began working on in Module Two. https://www.mediafire.com/file/d11ws1xz8axu65v/MBA_530_GROW_Afnan.Odhaib.docx/file

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use census data from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau.

In this homework assignment you will use census data from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau. A copy of this dataset is located at UCI Machine Learning 

Need help with Python programming

In this homework assignment you will use census data from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau. A copy of this dataset is located at UCI Machine Learning repository, please see this link to reach to the dataset website. This dataset contains census data extracted from the 1994 and 1995 Current Population Surveys. We will only work with ‘training’ data (a link to that is provided to you below). The data contains 41 demographic and employment related variables. The abbreviated column names provided to you below. You are expected to read the documentation of this dataset, understand the features and preprocess this dataset. Additional information can be found in the data description and additional comments. Below you will find a code snippet to download and read the data into a pandas dataframe. You can alternatively download it yourself, extract and read it manually. The questions are shown in the subsequent cells. You can provide your answers in this file. Make sure to change the notebook’s name and add your name before submitting. 

### Q1 – Identify the data scales and data types for each variable in census data. Identify the domain for each variable by checking the attributes’ values. Then, create a data quality report for both categorical (nominal, ordinal) and continuous (interval, ratio) variables. For data scales, identify whether an attribute is nominal, ordinal, interval or ratio scale. For data types, identify the domain and provide an appropriate data type (integer, float, String, date, Boolean). See if that data type is correct in your dataframe. For domain, inspect each distinct value for each attribute. Identify missing values. Also include the bar plots and histograms for visualizing the distributions. The examples for a continious and a categorical feature can be seen below. You do not need to use jupyter formatting provided here. You can print a DataFrame or read a csv, and display it. Make sure you have the csv in your zip file. 

Q2 – Identify the data quality issues for each attribute. Create a data quality plan and implement the changes. Identify missing values, potential anomalies and outliers. Finally, remedy these issues. 

Q3 – For all the interval and ratio scale features, create a scatter plot matrix (pairplots) and correlation matrix. For all ordinal scale features, create a correlation matrix using Spearman correlation. Use the data scales list you created in when creating a correlation matrix using Spearman rank, please use all features having an order (i.e., ordinal, interval, ratio scale variables) and not just ordinal features.  

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Categories
Writers Solution

census data from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau

In this homework assignment you will use census data from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau. A copy of this dataset is located at UCI Machine Learning re

Need help with Python programming

In this homework assignment you will use census data from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau. A copy of this dataset is located at UCI Machine Learning repository, please see this link to reach to the dataset website. This dataset contains census data extracted from the 1994 and 1995 Current Population Surveys. We will only work with ‘training’ data (a link to that is provided to you below). The data contains 41 demographic and employment related variables. The abbreviated column names provided to you below. You are expected to read the documentation of this dataset, understand the features and preprocess this dataset. Additional information can be found in the data description and additional comments. Below you will find a code snippet to download and read the data into a pandas dataframe. You can alternatively download it yourself, extract and read it manually. The questions are shown in the subsequent cells. You can provide your answers in this file. Make sure to change the notebook’s name and add your name before submitting. 

### Q1 – Identify the data scales and data types for each variable in census data. Identify the domain for each variable by checking the attributes’ values. Then, create a data quality report for both categorical (nominal, ordinal) and continuous (interval, ratio) variables. For data scales, identify whether an attribute is nominal, ordinal, interval or ratio scale. For data types, identify the domain and provide an appropriate data type (integer, float, String, date, Boolean). See if that data type is correct in your dataframe. For domain, inspect each distinct value for each attribute. Identify missing values. Also include the bar plots and histograms for visualizing the distributions. The examples for a continious and a categorical feature can be seen below. You do not need to use jupyter formatting provided here. You can print a DataFrame or read a csv, and display it. Make sure you have the csv in your zip file. 

Q2 – Identify the data quality issues for each attribute. Create a data quality plan and implement the changes. Identify missing values, potential anomalies and outliers. Finally, remedy these issues. 

Q3 – For all the interval and ratio scale features, create a scatter plot matrix (pairplots) and correlation matrix. For all ordinal scale features, create a correlation matrix using Spearman correlation. Use the data scales list you created in when creating a correlation matrix using Spearman rank, please use all features having an order (i.e., ordinal, interval, ratio scale variables) and not just ordinal features

GET SOLUTION BELOW

CLICK HERE TO MAKE YOUR ORDER

TO BE RE-WRITTEN FROM THE SCRATCH

NO PLAGIARISM

  • Original and non-plagiarized custom papers. Our writers develop their writing from scratch unless you request them to rewrite, edit or proofread your paper.
  • Timely Delivery. capitalessaywriting.com believes in beating the deadlines that our customers have imposed because we understand how important it is.
  • Customer satisfaction. Customer satisfaction. We have an outstanding customer care team that is always ready and willing to listen to you, collect your instructions and make sure that your custom writing needs are satisfied
  • Privacy and safety. It’s secure to place an order at capitalessaywriting.com We won’t reveal your private information to anyone else.
  • Writing services provided by experts. Looking for expert essay writers, thesis and dissertation writers, personal statement writers, or writers to provide any other kind of custom writing service?
  • Enjoy our bonus services. You can make a free inquiry before placing and your order and paying this way, you know just how much you will pay. A verdict was rendered against three parent chaperones. How was the third parent included in the case?
  • Premium papers. We provide the highest quality papers in the writing industry. Our company only employs specialized professional writers who take pride in satisfying the needs of our huge client base by offering them premium writing services census data from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau

Get Professionally Written Papers From The Writing Experts 

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