What is the number of derangements of size k from the set {1,2,...n} to the set {1,2,...n} so that f(x) != x exactly k times with 1 <= k <= n

Trace a State Space Tree introduced in the Chapter 5.1 using algorithms depth_first_search (page 205), checknode (page 207), and expand (page 210). Assume that State Space Tree is a two-level full binary tree (root is level 0). Node #2 (according to notation used in the Figure 5.1, page 204) is non-promising. Count the number of steps performed by each of those three algorithms. Consider execution of instructions like "visit node" or execution of "promising function" as one step, "write a solution" as an exit call. Note: no need to print or a draw a whole tree. Just provide three numbers as an answer

Parking Tickets Table St ID L_Name ☐ F_Name Phone_No St_Lic Lic_No Ticket# Date Code Fine 38249 38249 82453 Green 82453 Green 82453 Green Brown Thomas 111-7804 FL BRY 123 15634 10/17/06 2 25ドル Brown Thomas 111-7804 FL BRY 123 16017 11/13/06 1 15ドル Sally 391-1689 AL TRE 141 14987 10/05/06 3 100ドル Sally 391-1689 AL Sally 391-1689 AL TRE 141 TRE 141 16293 11/18/06 1 15ドル 17892 12/13/06 2 25ドル The functional dependencies are: St_ID → L_Name, F_Name, Phone_No, St_Lic, Lic_No St_Lic → Lic_No Code → Fine St_ID, Ticket # → Date 1. In what normal form is the relation?| 2. Convert PARKING TICKET to a set of 3NF relations.

In excel, What does sorting mean? In excel, What does filtering mean? What are three advantages of converting a range in Excel to a table and List the steps involved in creating a table in Excel if you were using the range A7:G34

Convert the relation Parking Tables to a set of 3NF relations.

Please original work What is the importance of understanding both DSS models and OLAP in modern business analytics. Reflect on how the combination of these tools can enhance decision-making processes in organizations. Please cite in text references and add weblinks

Please original work Talk about the role of Decision Support Systems (DSS) in business analytics. What are the major types of models used in DSS: optimization, simulation, forecasting, heuristic, and descriptive models. Talk about the relevance of these models in supporting business decisions. Please cite in text references and add weblinks

Please original work What are two DSS models (e.g., optimization and forecasting). What are each model’s purpose, advantages, and limitations in the context of business analytics. Talk about some examples of how each model can be applied in real-world business scenarios, particularly in operations, marketing, or finance. Please cite in text references and add weblinks

Please original work What is Online Analytical Processing (OLAP) and describe its role in DSS. Talk about how OLAP supports multidimensional analysis and decision-making in businesses. Compare how OLAP differs from traditional DSS models in terms of data processing and output. Please cite in text references and weblinks

Please original work Describe the key steps involved in the modeling process: problem definition, data collection, model formulation, validation, implementation, and refinement. Talk about why each step is critical to ensuring the accuracy and reliability of the model. What are some real-world business example of a problem, and describe how the modeling process could be applied to address it using DSS. Please cite in text references and add weblinks

You will be using the "usdata" package's "county" data # for this assignment. # You will need to run:# install.packages("usdata")# once to install this library - do not include the# install.packages command in your submission# as it can cause gradescope to fail ## ## ## ## ## DO NOT MODIFY BELOW ## ## ## ## ## library(usdata)county<-as.data.frame(county)county<-county[,1:14]county<-county[rowSums(is.na(county))==0,]# The set.seed command will ensure your results are consistent# each time you run the "source" commandset.seed(311)## ## ## ## ## DO NOT MODIFY ABOVE ## ## ## ## ## # Treating the "county" dataset as the population of US counties# create the dataframe "my.SRS" that represents a simple# random sample of n=250 individual counties from all counties in the US. my.SRS <- NA # Treating the "county" dataset as the population of US counties# create the dataframe "my.Stratified" that represents a stratified# sample of individual counties from all counties in...

Please answer two JAVA OOP problems.